CN113534152A - A signal processing method, device and computer-readable storage medium - Google Patents

Abstract

The embodiment of the present application discloses a signal processing method, the method includes: generating a first Chebyshev window function, and determining a first impulse response width of the first Chebyshev window function; determining a weight parameter, and based on the weight parameter Modify the edge points of the first Chebyshev window function to obtain the second Chebyshev window function; determine the first time-frequency function based on the second Chebyshev window function; determine the first time-frequency function based on the first time-frequency function and the first impulse The response width determines the target signal. The embodiments of the present application also disclose a signal processing device and a computer-readable storage medium.

Description

A signal processing method, device and computer-readable storage medium

technical field

The present application relates to signal processing technologies in the field of signal processing, and in particular, to a signal processing method, device, and computer-readable storage medium.

Background technique

Linear frequency modulation (LFM) signals are widely used in the mapping and imaging applications of spaceborne synthetic aperture radar (SAR) systems due to their high resolution, good Doppler tolerance and simple design. However, the peak sidelobe ratio (PSLR) of the autocorrelation function of the LFM signal is high, which will lead to a decrease in the clarity of the SAR image. In recent years, the nonlinear frequency modulation (NLFM) signal is complex and diverse. Freely adjusting the side lobe level of the autocorrelation function to reduce PSLR has gradually attracted the attention of scholars in the field of synthetic aperture radar.

In the related art, an existing window function is mainly processed based on the POSP algorithm in synthesizing an NLFM signal, and an NLFM signal with the impulse response property of the window function is obtained. However, the synthetic NLFM signal in the related art has low precision, resulting in a still high PSLR, which in turn makes the SAR image low in definition.

SUMMARY OF THE INVENTION

In order to solve the above technical problems, the embodiments of the present application expect to provide a signal processing method, device, and computer-readable storage medium, which solve the problem of low precision of synthesized NLFM signals.

The technical solution of the present application is realized as follows:

A signal processing method, the method comprising:

generating a first Chebyshev window function, and determining a first impulse response width of the first Chebyshev window function;

determining a weight parameter, and modifying the edge point of the first Chebyshev window function based on the weight parameter to obtain a second Chebyshev window function;

determining a first time-frequency function based on the second Chebyshev window function;

A target signal is determined based on the first time-frequency function and the first impulse response width.

In the above solution, generating the first Chebyshev window function and determining the first impulse response width of the first Chebyshev window function, including:

Obtain the target pulse width, the target sampling rate and the first peak-to-side lobe ratio;

Based on the target pulse width, the target sampling rate, and the first peak-to-sidelobe ratio, the first Chebyshev window function is generated, and the first impulse response width is determined.

In the above solution, the weight parameter is determined, and the edge point of the first Chebyshev window function is modified based on the weight parameter to obtain a second Chebyshev window function, including:

The first Chebyshev window function is analyzed to obtain a first target point and a second target point; wherein, the edge point includes the first target point and the second target point;

The position parameters of the first target point and the second target point are weighted based on each weight parameter to obtain a first weighted position parameter of the first target point and a second weighted value of the second target point. position parameter;

The position parameter of the first target point of the first Chebyshev window function is updated based on the first weighted position parameter, and all the position parameters of the first Chebyshev window function are updated based on the second weighted position parameter. The position parameter of the second target point is obtained to obtain the second Chebyshev window function.

In the above solution, determining the first time-frequency function based on the second Chebyshev window function includes:

Determine the target bandwidth;

Based on the target bandwidth, a stationary phase principle algorithm is used to process each of the second Chebyshev window functions to obtain a plurality of the first time-frequency functions.

In the above solution, determining the target signal based on the first time-frequency function and the first impulse response width includes:

processing each of the first time-frequency functions to determine a plurality of first signals;

determining a second peak-to-side lobe ratio and a second impulse response width for each of the first signals;

The target signal is determined from a plurality of the first signals based on the first impulse response width, the second peak-to-side lobe ratio, and the second impulse response width.

In the above solution, each of the first time-frequency functions is processed to determine a plurality of first signals, including:

Integrating each of the first time-frequency functions to obtain the plurality of first signals.

In the above solution, each of the first time-frequency functions is processed to determine a plurality of first signals, including:

Modifying each of the first time-frequency functions to obtain a plurality of second time-frequency functions;

The plurality of first signals are obtained by integrating each second time-frequency function.

In the above solution, each of the first time-frequency functions is modified to obtain a plurality of the second time-frequency functions, including:

Each first time-frequency function is analyzed to determine the position parameter of the connection point; wherein, the connection point is between the straight line corresponding to the linear function and the curve corresponding to the nonlinear function in the first time-frequency function. Junction;

determining an expression for the linear function in each of the first time-frequency functions;

Based on the expression of the linear function and the position parameter of the connection point, the position parameter of each point of the first time-frequency function is modified to obtain a plurality of second time-frequency functions.

In the above scheme, the position parameter of each point of the first time-frequency function is modified based on the expression of the linear function and the position parameter of the connection point to obtain a plurality of second time-frequency functions, include:

Determine the position parameter of the third target point based on the position parameter of the connection point and the expression;

Based on the first position parameter of the connection point and the first position parameter of the third target point, the first position parameter of the fourth target point is determined from the points of the nonlinear function; wherein the position parameter includes the first position parameter and the second position parameter;

Based on the expression and the first position parameter of the fourth target point, an updated second position parameter of the fourth target point is determined, and the updated position parameter is used to replace the description in the first time-frequency function The second position parameter of the fourth target point is obtained to obtain the plurality of second time-frequency functions.

In the above solution, the target signal is determined from a plurality of the first signals based on the first impulse response width, the second peak-to-side lobe ratio, and the second impulse response width, including:

determining a third impulse response width not greater than the first impulse response width from a plurality of second impulse response widths;

determining a second signal from the first signal based on the third impulse response width;

The target signal is obtained by determining the signal with the smallest second peak-to-side lobe ratio from the second signal.

A signal processing device, the device comprising: a processor, a memory and a communication bus;

The communication bus is used to realize the communication connection between the processor and the memory;

The processor is used to execute the signal processing program in the memory to realize the following steps:

generating a first Chebyshev window function, and determining a first impulse response width of the first Chebyshev window function;

determining a weight parameter, and modifying the edge point of the first Chebyshev window function based on the weight parameter to obtain a second Chebyshev window function;

determining a first time-frequency function based on the second Chebyshev window function;

A target signal is determined based on the first time-frequency function and the first impulse response width.

A computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the above signal processing method.

The signal processing method, device, and computer-readable storage medium provided by the embodiments of the present application generate a first Chebyshev window function, and determine a first impulse response width of the first Chebyshev window function; determine a weight parameter, and Modify the edge points of the first Chebyshev window function based on the weight parameters to obtain the second Chebyshev window function; determine the first time-frequency function based on the second Chebyshev window function; determine the first time-frequency function based on the first time-frequency function and the Determine the target signal by the width of the impulse response; in this way, the edge point of the first Chebyshev window function can be modified to avoid distortion caused by the edge point when the first Chebyshev window function generates the target signal, resulting in the synthesis of the target signal. The accuracy is low, the accuracy of the synthesized target signal is improved, the peak-to-side lobe ratio of the synthesized target signal is further reduced, and the clarity of the SAR image is improved.

Description of drawings

FIG. 1 is a schematic flowchart of a signal processing method provided by an embodiment of the present application;

FIG. 2 is a schematic flowchart of a signal processing method provided by another embodiment of the present application;

3 is a schematic diagram of a simulation result of a first Chebyshev window provided in an embodiment of the present application;

4 is a schematic diagram of a simulation result of a signal processing method provided by an embodiment of the present application;

5 is a schematic diagram of a simulation result of another signal processing method provided by an embodiment of the present application;

6 is a schematic diagram of a simulation result of another signal processing method provided by an embodiment of the present application;

FIG. 7 is a schematic diagram of a simulation result of another signal processing method provided by an embodiment of the present application;

8 is a schematic diagram of a simulation result of another signal processing method provided by an embodiment of the present application;

FIG. 9 is a schematic flowchart of a signal processing method provided by another embodiment of the present application;

10 is a schematic diagram of a simulation of a first time-frequency function of a signal processing method according to another embodiment of the present application;

11 is a schematic flowchart of a signal processing method provided by another embodiment of the present application;

12 is a comparison diagram of a simulation result of a signal processing method provided by another embodiment of the application;

FIG. 13 is a schematic structural diagram of a signal processing device according to another embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application.

It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

An embodiment of the present application provides a signal processing method, which is applied to a signal processing device. As shown in FIG. 1 , the method includes the following steps:

Step 101: Generate a first Chebyshev window function, and determine a first impulse response width of the first Chebyshev window function.

In this embodiment of the present application, the signal processing device may be loaded with Matrix Laboratory software (MatrixLaboratory, Matlab), where Matlab is used for data analysis, wireless communication, deep learning, image processing and computer vision, signal processing, and the like.

Specifically, the signal processing device may receive the input generation instruction, generate the first Chebyshev window function through Matlab, and calculate the first impulse response width of the first Chebyshev window function. The generating instruction is used to instruct the signal processing device to generate the first Chebyshev window function, and the generating instruction may also carry parameters representing the size of the first Chebyshev window function and the peak-to-side lobe ratio of the first Chebyshev window function The generation instruction may be sent by the user to the signal processing device through the terminal, or may be generated by the signal processing device by detecting the user's input operation and according to the user's input operation.

It should be noted that, according to the properties of the first Chebyshev window function, when the impulse response width (IRW) is fixed, the PSLR of the first Chebyshev window function is the lowest. Generate the target signal, but since the first Chebyshev window function generates the target signal, distortion will appear at a specific point of the target signal, so in order to further improve the accuracy of generating the target signal, before generating the target signal, you can The Bishev window function is processed to avoid distortion at specific points of the generated target signal. Among them, the specific point may correspond to the edge point of the first Chebyshev window function.

Step 102: Determine the weight parameter, and modify the edge point of the first Chebyshev window function based on the weight parameter to obtain the second Chebyshev window function.

The weight parameter may also be called a weight modification factor or a weighting coefficient; the edge points are two points on the edge of the first Chebyshev function; the first Chebyshev window function is a discrete function.

In this embodiment of the present application, the weight parameter may be used to modify the position parameter of the edge point of the first Chebyshev window function, and the second edge point may be generated based on the modified position parameter of the edge point and the first Chebyshev window function. Byshev window function.

In a feasible implementation, if the size of the first Chebyshev window function is 6, the first Chebyshev number window function can be expressed by formula (1):

w ₁ =(w[0],w[1],w[2],w[3],w[4],w[5]) Formula (1)

Among them, w ₁ represents the first Chebyshev window function, and w[0] and w[5] are edge points.

Step 103: Determine a first time-frequency function based on the second Chebyshev window function.

In this embodiment of the present application, the POSP algorithm may be used to process the second Chebyshev window function to obtain the first time-frequency function. Wherein, the first time-frequency function is used to represent the function of the corresponding relationship between time and frequency.

Step 104: Determine the target signal based on the first time-frequency function and the first impulse response width.

In the embodiment of the present application, the first time-frequency function can be converted to obtain an alternative signal, and the alternative signal can be screened by the first impulse response width to determine the target signal; wherein, the target signal is a nonlinear frequency modulation signal .

It should be noted that, if the number of candidate signals is one, the candidate signal may be used as the target signal, and if the number of candidate signals is multiple, the most optimal signal may be determined from the candidate signals based on the first impulse response width. The optimal signal is used as the target signal. Among them, in the case of the same main lobe width, the PSLR of the candidate signal is significantly lower than the PSLR of the nonlinear FM signal obtained in the related art. By screening the candidate signal, the accuracy of the obtained target signal can be further improved. .

The signal processing method provided by the embodiment of the present application can modify the edge point of the first Chebyshev window function, so as to avoid the accuracy of the synthesized target signal caused by distortion caused by the edge point when the first Chebyshev window function generates the target signal Low, which improves the precision of the synthesized target signal, further reduces the peak-to-side lobe ratio of the synthesized target signal, and improves the clarity of the SAR image.

Based on the foregoing embodiments, an embodiment of the present application provides a signal processing method, as shown in FIG. 2 , the method includes:

Step 201: The signal processing device acquires the target pulse width, the target sampling rate and the first peak-to-sidelobe ratio.

The target pulse width, the target sampling rate and the first peak-to-sidelobe ratio can all be parameters carried in the generation instruction; the target pulse width, the target sampling rate and the first peak-to-sidelobe ratio can be determined by the user based on the clarity of the SAR image. definite.

Step 202: The signal processing device generates a first Chebyshev window function based on the target pulse width, the target sampling rate and the first peak-to-side lobe ratio, and determines the first impulse response width.

In the embodiment of the present application, the signal processing device generates the first Chebyshev window function through Matlab based on the target pulse width, the target sampling rate and the first peak side lobe ratio; wherein, the peak side lobe of the first Chebyshev window function The ratio is the first peak-to-side lobe ratio, and the size of the first Chebyshev window function is the product of the target pulse width and the target sampling rate.

Among them, the target pulse width can be represented by T, the target sampling rate can be represented by Fr, the first peak sidelobe ratio can be represented by R; the length (ie size) of the first Chebyshev window function can be represented by formula (2 )To represent:

表示向下取整操作。where N is the length of the first Chebyshev window,

Indicates a round-down operation.

According to the definition of the Chebyshev window function, the size is N, without loss of generality, let N be an even number, let N=2M, M be a positive integer, and the first Chebyshev window function whose peak sidelobe ratio is R uses the formula ( 3) and Figure 3 to represent;

T_2M(x)为切比雪夫多项式，用公式(4)表示为：Wherein, w _n represents the first Chebyshev window function; n and m are integers, θ _n =(2n+1)π/N, θ _m =2πm/N,

T _2M (x) is the Chebyshev polynomial, which is expressed as:

Among them, the first impulse response of the first Chebyshev window function can be expressed as:

s=F _p W formula (5)

Among them, s represents the first impulse response; F _p is the inverse Fourier transform matrix of N×N; among them, N is the size of the first Chebyshev window function, and W represents the transpose of the first Chebyshev window function . W and F _p can be expressed by formula (6) and formula (7), respectively:

W=[w _-M ,...,w ₀ ,...,w _M-1 ] ^T formula (6)

In the embodiment of the present application, when determining the first impulse response width of the first Chebyshev window function, firstly, it is necessary to perform P times upsampling on the first Chebyshev window function, and obtain the first time after the P times upsampling. The Byshev window function (the length of the first Byshev window function becomes PN, and P represents a multiple) is expressed by formula (8) as:

W ₀ =[0,0,...,0,w _-M ,...,w ₀ ,...,w _M-1 ] ^T formula (8)

Among them, W ₀ represents the first Chebyshev window function after upsampling by P times, and inverse Fourier transform is performed on W ₀ to obtain the impulse response after upsampling, as shown in Figure 4, at the abscissas 3 and 4 The black part in between is the main lobe. After enlarging the main lobe part in Figure 4, as shown in Figure 5, the middle part represents the main lobe, and the width of the first impulse response is N ₀ /P; where N ₀ is The rectangular part in the middle represents the number of abscissa sampling points.

Step 203: The signal processing device analyzes the first Chebyshev window function to obtain the first target point and the second target point.

The edge points include a first target point and a second target point.

In this embodiment of the present application, Maltab can be used to analyze the position parameters of multiple points in the first Chebyshev window function to determine two points on the edge of the first Chebyshev window function, that is, the first target point and the first Chebyshev window function. Two target points.

Step 204: The signal processing device performs weighting processing on the position parameters of the first target point and the second target point based on each weight parameter to obtain the first weighted position parameter of the first target point and the second weighted position parameter of the second target point. .

Wherein, the position parameter includes a first position parameter and a second position parameter.

In the embodiment of the present application, for any weight parameter, the weight parameter can be multiplied by the second position parameter of the first target point to obtain the first value, and the first value is used to replace the second position parameter of the first target point. The position parameter is to obtain the weighted position parameter of the first target point, wherein the weighted position parameter of the first target point includes the first position parameter and the first value of the first target point; The second value is obtained by multiplying the two position parameters, and the second value is used to replace the second position parameter of the second target point to obtain the weighted position parameter of the second target point, wherein the weighted position parameter of the second target point includes the second target point The first position parameter and second value of the point. The first position parameter may represent the abscissa of the midpoint of the first Chebyshev window function; the second position parameter may represent the ordinate of the midpoint of the second Chebyshev function. The weight parameter can be represented by α, and the value range of α is [1.8, 3].

It should be noted that within the value range of [1.8, 3], multiple weight parameters can be obtained. For each weight parameter, the first target point and the second target point need to be weighted, so that the target can be generated later. signal; where the number of weight parameters corresponds to the number of second Chebyshev window functions.

Step 205: The signal processing device updates the position parameter of the first target point of the first Chebyshev window function based on the first weighted position parameter, and updates the position parameter of the second target point of the first Chebyshev window function based on the second weighted position parameter. positional parameters to obtain the second Chebyshev window function.

Wherein, each weighting parameter may correspond to a second Chebyshev window function.

In this embodiment of the present application, the first weighted position parameter may be substituted for the position parameter of the first target point in the first Chebyshev function, and the second weighted position parameter may be substituted for the position parameter of the second target point in the first Chebyshev function. positional parameters to obtain the second Chebyshev window function.

In a feasible implementation manner, if the size of the first Chebyshev window function is 6, the first Chebyshev window function can be expressed by formula (1) as:

w ₁ =(w[0],w[1],w[2],w[3],w[4],w[5]) Formula (1)

where w ₁ represents the first Chebyshev window function, w[0] and w[5] are edge points, the first position parameter of w[0] is "0", and the second position parameter of w[0] is w[0]; the first position parameter of w[5] is "5", and the second position parameter of w[5] is w[5]; then the second Chebyshev window function can be represented by formula (9) :

w ₂ =(αw[0],w[1],w[2],w[3],w[4],αw[5]) Formula (9)

Wherein, w ₂ represents the second Chebyshev window function, αw[0] represents the first value in the first weighted position parameter of the edge point "0", and αw[5] represents the second weighted position of the edge point "5" the second value in the parameter; or, αw[5] represents the first value in the first weighted position parameter of the edge point "5", and αw[0] represents the first value in the second weighted position parameter of the edge point "0" binary value.

Step 206: The signal processing device determines the target bandwidth.

The target bandwidth is determined based on a bandwidth parameter, and the bandwidth parameter is a preset bandwidth of the target signal to be generated.

Wherein, the target bandwidth is the target function interval of the second Chebyshev window function.

In a feasible implementation manner, if the bandwidth parameter is represented by B, the target bandwidth may be [-B/2, B/2].

Step 207: The signal processing device uses the stationary phase principle algorithm to process each second Chebyshev window function based on the target bandwidth to obtain a plurality of first time-frequency functions.

Among them, the idea of the principle of stationary phase (POSP) algorithm is to shape the window function shape of the power spectral density (PSD) of the NLFM signal, so that the autocorrelation function of the NLFM signal has a window function impulse response nature.

In the embodiment of the present application, the second Chebyshev window function is processed by the POSP algorithm, and the obtained PSD of the NLFM signal with a pulse width of T and a bandwidth of B can be represented by formula (10):

Among them, P(f) represents the power spectral density of the nonlinear FM signal; θ″(t ₀ ) represents the second-order derivative function of θ(t) at t=t ₀ , and θ(t) is a continuous phase function; where, t ₀ is determined by formula (11).

θ′(t ₀ )=2πf Formula (11)

Among them, f represents the frequency of the nonlinear FM signal, θ′(t ₀ ) represents the first-order derivative function of θ(t) at t=t ₀ , and G(f) is the Fresnel integral term, which can be calculated by formula (12) )To represent:

K(x)表示菲涅尔积分函数，通常G(f)可以粗略地近似为矩形函数，即可以用公式(13)表示为：in,

K(x) represents the Fresnel integral function, and usually G(f) can be roughly approximated as a rectangular function, that is, it can be expressed by formula (13) as:

Among them, B represents the bandwidth of the nonlinear FM signal.

The shape of the PSD shaping window function of the NLFM signal is expressed by formula (14):

where W(f) is the second Chebyshev window function, the group delay function can be obtained from formula (11) and formula (14), and the group delay function can be expressed by formula (15):

where C is a constant, which can be expressed by Equation (16):

Converting the group delay function (formula (15)), the first time-frequency function can be obtained, where the first time-frequency function can be expressed by formula (17):

It should be noted that the ideal performance of the autocorrelation function of the nonlinear FM signal is as narrow as possible IRW, as low as possible PSLR and rapidly decreasing sidelobe fluctuation envelope, but these three ideal performances cannot be satisfied simultaneously. According to the properties of the Chebyshev window function, when the IRW is fixed, the PSLR of the impulse response of the Chebyshev window function is the lowest. Therefore, according to the idea of the POSP algorithm, if the Chebyshev window function is selected to generate the NLFM signal, then the PSLR of the autocorrelation function of the NLFM signal should be the lowest when the IRW (impulse response width) is fixed. However, due to the edge distortion effect, the autocorrelation function of the Chebyshev window NLFM signal no longer meets the performance of the Chebyshev window impulse response. Therefore, before the first Chebyshev window function is processed by the POSP algorithm, the Chebyshev window It is very necessary to modify the function, which can avoid the edge distortion of the target signal and further improve the accuracy of the determined target signal.

Step 208: The signal processing device processes each first time-frequency function to determine a plurality of first signals.

In this embodiment of the present application, each first time-frequency function may be processed and analyzed to obtain a first signal corresponding to each time-frequency function.

Wherein, a plurality of first signals can be used as candidate signals, so that the target signal can be subsequently determined from the candidate signals.

It should be noted that, in this embodiment of the present application, step 208 may be implemented by a or b1-b2;

a1. The signal processing device integrates each first time-frequency function to obtain a plurality of first signals.

In the embodiment of the present application, each first time-frequency function is integrated to obtain a plurality of first signals, wherein the first signals are nonlinear frequency modulation signals.

Among them, the first signal can be expressed by formula (18):

Among them, T is the pulse width of the signal, and t refers to the time; rect(·) is a rectangular function.

b1. The signal processing device modifies each first time-frequency function to obtain a plurality of second time-frequency functions.

Specifically, the linear function part and the nonlinear function part in the first time-frequency function can be modified, so that the linear function part in the second time-frequency function obtained after modification is more than the linear function part in the first time-frequency function .

It should be noted that before the first time-frequency function is obtained, the edge points of the first Chebyshev window function are weighted. Although the edge distortion caused by the POSP algorithm can be reduced to a certain extent, the final target signal has The power spectrum is not completely equivalent to the power spectrum of the Chebyshev window function. In order to further improve the accuracy of the obtained target signal, the nonlinearity in the first time-frequency function can be reduced by increasing the linear function part of the first time-frequency function. function part to achieve.

b2. The signal processing device integrates each second time-frequency function to obtain a plurality of first signals.

The implementation process of b2 is the same as the implementation process of a1, and details are not described herein again in this embodiment of the present application.

Step 209: The signal processing device determines the second peak-to-sidelobe ratio and the second impulse response width of each candidate signal.

In this embodiment of the present application, Fourier transform may be performed on the first signal to obtain a spectrum of the first signal, then the power spectrum of the first signal may be determined by using the spectrum of the first signal, and Fourier transform may be performed on the first signal Inverse transform to get the result of the autocorrelation function.

In a feasible implementation manner, the frequency of the first signal is S(f), then the power spectrum of the first signal is P(f)=|S(f)| ² , where P(f) represents the first signal The power spectrum of the signal, and then perform the inverse Fourier transform on P(f) to obtain the result of the autocorrelation function y(t); among them, the power spectrum of the first signal can be represented by Figure 6, if the power spectrum is in discrete form is P=[P ₁ ,...,P _N ], the length is N, and the Q-fold upsampling is performed on the power spectrum with zero padding as P _u =[0,0,...,0,P ₁ ,...,P _N ], the length is is QP, and then inverse Fourier transform is performed on P _u , the autocorrelation function result after upsampling can be obtained, wherein the autocorrelation function result after upsampling can be represented by Figure 7, wherein the second impulse response width Similar to the process of acquiring the first impulse response width, this embodiment of the present application will not describe it again. FIG. 8 is an enlarged schematic diagram of the middle part of FIG. 7 , and the second peak-to-side lobe ratio refers to the ratio of the value of the highest point of the side lobe part to the value of the highest point of the main lobe part in FIG. 8 .

Step 210: The signal processing device determines a target signal from the plurality of first signals based on the first impulse response width, the second peak-to-side lobe ratio, and the second impulse response width.

In this embodiment of the present application, the second signal may be determined from the candidate signals based on the first impulse response width and the second impulse response width, and then based on the side lobe ratio of each candidate signal, the second signal may be determined from multiple candidate signals. The target signal is determined in the second signal.

Wherein, step 210 can be realized by steps a2-a4;

a2. The signal processing device determines a third impulse response width that is not greater than the first impulse response width from the plurality of second impulse response widths.

Wherein, the third impulse response width is less than or equal to the first impulse response width.

a3. The signal processing device determines the second signal from the first signal based on the third impulse response width.

In the embodiment of the present application, the signal processing device determines a signal of the third impulse response width from the first signal, and uses the signal of the third impulse response width as the second signal.

a4. The signal processing device determines the signal with the smallest second peak-to-side lobe ratio from the second signal to obtain the target signal.

In this embodiment of the present application, after the second signal is obtained, the second peak-to-side lobe ratios of multiple second signals may be sorted, and the smallest second peak-to-side lobe ratio is determined from the sorted multiple second peak-to-side lobe ratios Lobe ratio, and take the signal with the smallest second peak side lobe as the target signal. Wherein, the pulse width of the target signal is the target pulse width; the bandwidth of the target signal is the target bandwidth.

The signal processing method provided by the embodiment of the present application can modify the edge point of the first Chebyshev window function, so as to avoid the accuracy of the synthesized target signal caused by distortion caused by the edge point when the first Chebyshev window function generates the target signal Low, which improves the precision of the synthesized target signal, further reduces the peak-to-side lobe ratio of the synthesized target signal, and improves the clarity of the SAR image.

Based on the foregoing embodiments, an embodiment of the present application provides a signal processing method. As shown in FIG. 9 , the method includes:

Step 301: The signal processing device acquires a target pulse width, a target sampling rate and a first peak-to-sidelobe ratio.

Step 302: The signal processing device generates a first Chebyshev window function based on the target pulse width, the target sampling rate and the first peak-to-side lobe ratio, and determines the first impulse response width.

Step 303: The signal processing device analyzes the first Chebyshev window function to obtain the first target point and the second target point.

The edge points include a first target point and a second target point.

Step 304: The signal processing device performs weighting processing on the position parameters of the first target point and the second target point based on each weight parameter to obtain the first weighted position parameter of the first target point and the second weighted position parameter of the second target point. .

Step 305: The signal processing device updates the position parameter of the first target point of the first Chebyshev window function based on the first weighted position parameter, and updates the position parameter of the second target point of the first Chebyshev window function based on the second weighted position parameter. positional parameters to obtain the second Chebyshev window function.

Step 306: The signal processing device determines the target bandwidth.

Step 307: The signal processing device uses the stationary phase principle algorithm to process each second Chebyshev window function based on the target bandwidth to obtain a first time-frequency function.

Step 308: The signal processing device analyzes each first time-frequency function to determine the position parameter of the connection point.

The connection point is the connection point between the straight line corresponding to the linear function and the curve corresponding to the nonlinear function in the first time-frequency function. The first time-frequency function is a discrete function.

In the embodiment of the present application, the variation law of the position parameters of multiple points in the first time-frequency function can be analyzed to determine the difference between the straight line corresponding to the linear function in the first time-frequency function and the curve corresponding to the nonlinear function connection point between. Wherein, the connection point may be at least one.

In a feasible implementation manner, the number of connection points is two. As shown in FIG. 10 , the linear function in the first time-frequency function corresponds to two straight lines, and the two straight lines correspond to a curve, and the curve is the first time-frequency function. A curve corresponding to a nonlinear function in a time-frequency function, the two points where the curve and the two straight lines intersect are determined two connection points. It should be noted that the first connection point and the second connection point are center-symmetrical, and after the first connection point is determined, the second connection point can be determined according to the center symmetry.

In the embodiment of the present application, a differential operation can be performed on the first time-frequency function, and the position parameter of the connection point can be determined from the result of the differential operation; the straight line corresponding to the linear function and the curve corresponding to the nonlinear function can also be analyzed. to determine the location parameters of the connection point.

In a feasible implementation manner, the discrete form of the first time-frequency function is f ₀ =[f ₁ ,f ₂ ,...,f _N ], and the difference operation is performed on f ₀ to obtain df ₀ =[f ₂ -f ₁ ,f ₃ -f ₂ ,…,f _N -f _N-1 )], then the point that maximizes df ₀ is taken as the connection point, and the position parameter of the connection point is determined according to the expression of the linear function.

Step 309: The signal processing device determines the expression of the linear function in each first time-frequency function.

In this embodiment of the present application, the point (function point) corresponding to the linear function in the first time-frequency function may be determined based on the determined position parameter of the connection point, any two points may be determined from the linear function, and according to the determined The position parameters of the two points are used to determine the slope of the linear function, and the expression of the linear function is obtained according to the position parameters and slopes of other points in the linear function.

The position parameter of the connection point is the connection point between the straight line corresponding to the linear function and the curve corresponding to the nonlinear parameter.

Step 310 , the signal processing device modifies the position parameter of each point of the first time-frequency function based on the expression of the linear function and the position parameter of the connection point to obtain a plurality of second time-frequency functions.

Wherein, the position parameter of the point of the first time-frequency function refers to the position parameter of the partial point of the nonlinear function of the first time-frequency function.

Wherein, step 310 can be implemented by c1-c3:

c1. The signal processing device determines the position parameter of the third target point based on the position parameter and the expression of the connection point.

In the embodiment of the present application, the first position parameter of the position parameter of the third target point may be determined according to the first position parameter of the position parameter of the connection point, and then the first position parameter of the position parameter of the third target point is substituted into In the expression, the second position parameter of the third target point is obtained; wherein, the position parameter of the third target point includes the first position parameter of the third target point and the second position parameter of the third target point.

c2, the signal processing device determines the first position parameter of the fourth target point from the points of the nonlinear function based on the first position parameter of the connection point and the first position parameter of the third target point; wherein, the position parameter includes the first position parameters and second positional parameters.

The fourth target point is a point between the connection point in the nonlinear function and the third target point.

In this embodiment of the present application, the fourth target point between the connection point and the third target point may be determined from the points of the nonlinear function based on the first position parameter of the connection point and the first position parameter of the third target point, Then, the first position parameter of the fourth target point is determined from the position parameters of the point of the nonlinear function.

Specifically, the first position parameter can be substituted into the expression to obtain the second position parameter to be updated of the fourth target point.

c3, the signal processing device determines the updated second position parameter of the fourth target point based on the expression and the first position parameter of the fourth target point, and uses the updated position parameter to replace the second position parameter of the fourth target point in the first time-frequency function position parameter to obtain multiple second time-frequency functions.

In the embodiment of the present application, for any first time-frequency function, the updated second position parameter of the fourth target point is obtained by substituting the first position parameter of the fourth target point into the expression of the linear function, And replace the second position parameter of the fourth target point in the nonlinear function with the updated second position parameter to obtain the second time-frequency function.

Step 311: The signal processing device determines, from the plurality of second impulse response widths, a third impulse response width that is not greater than the first impulse response width.

The third impulse response width is a signal obtained by screening multiple second impulse response widths, so that the target signal is subsequently determined according to the third impulse response width, which can further improve the accuracy of the determined target signal.

Step 312: The signal processing device determines the second signal from the first signal based on the third impulse response width.

In this embodiment of the present application, a signal with the same width as the third impulse response may be determined from the first signal, and the signal may be used as the second signal; wherein the impulse response width of the second signal is the same as the third impulse response width. same width.

Step 313: The signal processing device determines the signal with the smallest second peak-to-sidelobe ratio from the second signal to obtain the target signal.

In this embodiment of the present application, when the weight parameter is changed, the position parameter of the connection point, the second peak-to-side lobe ratio, and the second impulse response width will all change; the peak-to-side lobe ratio of the second signal is smaller than that determined in the related art The peak-to-side lobe ratio of the nonlinear FM signal, at this time, the second signal is screened again to obtain the signal with the smallest peak-to-side lobe ratio in the second signal, and this signal is used as the target signal, which further ensures the determined target signal. , so that the peak-to-side lobe ratio of the target signal can be optimized, and the clarity of the SAR image is improved.

It should be noted that, for the description of the same steps and the same content in this embodiment as in other embodiments, reference may be made to the descriptions in other embodiments, and details are not repeated here.

As shown in FIG. 11 , the signal processing device generates a first Chebyshev window function based on the first peak-to-sidelobe ratio, the target pulse width, and the target sampling rate, and calculates the first impulse response width of the first Chebyshev window function IRW0, through each weight parameter of multiple weight parameters α, weight modification (weighted processing) is performed on the first Chebyshev window function to obtain multiple second Chebyshev window functions, and then the POSP algorithm is used for each second Chebyshev window function. The _Bishev window function is processed to obtain a plurality of first time-frequency functions; each first time-frequency function is analyzed to determine the slope Kp of the linear function (linear component) in the first time-frequency function and the first time-frequency function The position _parameter of the connection point _Nt of the _linear function and the nonlinear function in The position parameter of the target point (N _t +N _i ); wherein, N _i is less than N _t , and N _i is greater than or equal to 1, then the position parameter of the point between the connection point and the third target point is modified to obtain the second Time-frequency function, integrating the second time-frequency function to obtain the first signal.

It should be noted that the weight parameter α and the connection point Ni are both variables, and the calculated impulse response width IRW and peak sidelobe ratio _PSLR of the first signal will also change when α and _Ni change. Each weight parameter α corresponds to a first signal, that is to say, a plurality of first signals can be finally obtained, and the IRW and PSLR in each first signal are determined, and the obtained first impulse response width IRW0, The IRW and PSLR of the first signal are used to screen the first signal. Specifically, a second signal satisfying IRW≤IRW0 may be selected from the first signal, and then a signal with the smallest PSLR may be selected from the second signal as the target signal.

As shown in Figure 12, it is the second peak sidelobe ratio and the second impulse response width of the target signal generated by the second Chebyshev window function, and the peak sidelobe ratio and the impulse response width of the target signal generated by other window functions. The comparison result of the response width shows that the peak-to-side lobe ratio of the second Chebyshev window function is lower than the peak-to-side lobe ratio of the target signal generated by other window functions, that is to say, the generated target signal is better than other window functions. The target signal generated by the window function.

The signal processing method provided by the embodiment of the present application can modify the edge point of the first Chebyshev window function, so as to avoid the accuracy of the synthesized target signal caused by distortion caused by the edge point when the first Chebyshev window function generates the target signal Low, which improves the precision of the synthesized target signal, further reduces the peak-to-side lobe ratio of the synthesized target signal, and improves the clarity of the SAR image.

Based on the foregoing embodiments, an embodiment of the present application further provides a signal processing device, which can be applied to the signal processing methods provided by the embodiments corresponding to FIG. 1 , FIG. 2 , and FIG. 9 . Referring to FIG. 13 , the signal processing device The processing device 4 includes: a processor 41, a memory 42 and a communication bus 43;

The communication bus 43 is used to realize the communication connection between the processor 41 and the memory 42;

The processor 41 is used for executing the signal processing program in the memory 42 to realize the following steps:

generating the first Chebyshev window function, and determining the first impulse response width of the first Chebyshev window function;

Determine the weight parameter, and modify the edge point of the first Chebyshev window function based on the weight parameter to obtain the second Chebyshev window function;

determining the first time-frequency function based on the second Chebyshev window function;

The target signal is determined based on the first time-frequency function and the first impulse response width.

In other embodiments of the present application, the processor 41 is configured to execute the signal processing program in the memory 42 to generate the first Chebyshev window function, and to determine the first impulse response width of the first Chebyshev window function, so as to Implement the following steps:

Obtain the target pulse width, the target sampling rate and the first peak-to-side lobe ratio;

Based on the target pulse width, the target sampling rate, and the first peak-to-sidelobe ratio, a first Chebyshev window function is generated, and a first impulse response width is determined.

In other embodiments of the present application, the processor 41 is configured to execute the determined weight parameter of the signal processing program in the memory 42, and based on the weight parameter, modify the edge point of the first Chebyshev window function to obtain the second cut ratio Shef window function to implement the following steps:

The first Chebyshev window function is analyzed to obtain the first target point and the second target point; wherein, the edge point includes the first target point and the second target point;

Perform weighting processing on the position parameters of the first target point and the second target point based on each weight parameter to obtain the first weighted position parameter of the first target point and the second weighted position parameter of the second target point;

The position parameter of the first target point of the first Chebyshev window function is updated based on the first weighted position parameter, and the position parameter of the second target point of the first Chebyshev window function is updated based on the second weighted position parameter to obtain the second Chebyshev window function.

In other embodiments of the present application, the processor 41 is configured to execute the signal processing program in the memory 42 based on the second Chebyshev window function, and determine the first time-frequency function to realize the following steps:

Determine the target bandwidth;

Based on the target bandwidth, the stationary phase principle algorithm is used to process each second Chebyshev window function to obtain a plurality of first time-frequency functions.

In other embodiments of the present application, the processor 41 is configured to execute the signal processing program in the memory 42 to determine the target signal based on the first time-frequency function and the first impulse response width, so as to realize the following steps:

processing each first time-frequency function to determine a plurality of first signals;

determining a second peak-to-sidelobe ratio and a second impulse response width for each first signal;

A target signal is determined from the plurality of first signals based on the first impulse response width, the second peak-to-sidelobe ratio, and the second impulse response width.

In other embodiments of the present application, the processor 41 is configured to process each first time-frequency function of the signal processing program in the memory 42 to determine a plurality of first signals, so as to realize the following steps:

Each first time-frequency function is integrated to obtain a plurality of first signals.

In other embodiments of the present application, the processor 41 is configured to process each first time-frequency function of the signal processing program in the memory 42, and determine a plurality of first signals to implement the following steps:

Modifying each first time-frequency function to obtain a plurality of second time-frequency functions;

Each second time-frequency function is integrated to obtain a plurality of first signals.

In other embodiments of the present application, the processor 41 is configured to modify each first time-frequency function by executing the signal processing program in the memory 42 to obtain a plurality of second time-frequency functions, so as to realize the following steps:

Each first time-frequency function is analyzed to determine the position parameter of the connection point; wherein, the connection point is the connection point between the straight line corresponding to the linear function and the curve corresponding to the nonlinear function in the first time-frequency function;

determining an expression for the linear function in each first time-frequency function;

Based on the expression of the linear function and the position parameter of the connection point, the position parameter of each point of the first time-frequency function is modified to obtain a plurality of second time-frequency functions.

In other embodiments of the present application, the processor 41 is configured to execute the linear function-based expression of the signal processing program in the memory 42 and the position parameter of the connection point, and perform the operation on the position parameter of each point of the first time-frequency function. Modification to obtain multiple second time-frequency functions to achieve the following steps:

Determine the position parameter of the third target point based on the position parameter and expression of the connection point;

Based on the first position parameter of the connection point and the first position parameter of the third target point, the first position parameter of the fourth target point is determined from the points of the nonlinear function; wherein the position parameter includes the first position parameter and the second position parameter;

Based on the expression and the first position parameter of the fourth target point, the updated second position parameter of the fourth target point is determined, and the updated position parameter is used to replace the second position parameter of the fourth target point in the first time-frequency function. a second time-frequency function.

In other embodiments of the present application, the processor 41 is configured to execute the signal processing program in the memory 42 based on the first impulse response width, the second peak-to-side lobe ratio and the second impulse response width, from a plurality of first impulse response widths. Determine the target signal in the signal to achieve the following steps:

determining a third impulse response width not greater than the first impulse response width from the plurality of second impulse response widths;

determining the second signal from the first signal based on the third impulse response width;

The target signal is obtained by determining the signal with the smallest second peak-to-side lobe ratio from the second signal.

In the signal processing device provided by the embodiment of the present application, the edge points of the first Chebyshev window function can be modified, so as to avoid distortion caused by the edge points when the first Chebyshev window function generates the target signal, resulting in the synthesis of the target signal. The accuracy is low, the accuracy of the synthesized target signal is improved, the peak-to-side lobe ratio of the synthesized target signal is further reduced, and the clarity of the SAR image is improved.

Based on the foregoing embodiments, embodiments of the present application provide a computer-readable storage medium, where the computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to The steps of implementing the signal processing method provided by the embodiments corresponding to FIG. 1 , FIG. 2 , and FIG. 9 are implemented.

It should be noted that the above-mentioned computer-readable storage medium may be a read-only memory (Read Only Memory, ROM), a programmable read-only memory (Programmable Read-Only Memory, PROM), an erasable programmable read-only memory (Erasable Programmable read only memory, ROM) Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Magnetic Random Access Memory (FRAM), Flash Memory (Flash Memory) , magnetic surface memory, optical disk, or memory such as Compact Disc Read-Only Memory (CD-ROM); it can also be a variety of electronic devices including one or any combination of the above memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc.

It should be noted that, herein, the terms "comprising", "comprising" or any other variation thereof are intended to encompass non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements, It also includes other elements not expressly listed or inherent to such a process, method, article or apparatus. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in a process, method, article or apparatus that includes the element.

The above-mentioned serial numbers of the embodiments of the present application are only for description, and do not represent the advantages or disadvantages of the embodiments.

From the description of the above embodiments, those skilled in the art can clearly understand that the method of the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is better implementation. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence or in a part that contributes to the prior art, and the computer software product is stored in a storage medium (such as ROM/RAM, magnetic disk, CD-ROM), including several instructions to make a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in the various embodiments of this application.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

The above are only the preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the contents of the description and drawings of the present application, or directly or indirectly applied in other related technical fields , are similarly included within the scope of patent protection of this application.

Claims (12)

1. A signal processing method, wherein the method comprises: generating a first Chebyshev window function, and determining a first impulse response width of the first Chebyshev window function; determining a weight parameter, and modifying the edge point of the first Chebyshev window function based on the weight parameter to obtain a second Chebyshev window function; determining a first time-frequency function based on the second Chebyshev window function; A target signal is determined based on the first time-frequency function and the first impulse response width. 2. method according to claim 1, is characterized in that, described generating first Chebyshev window function, and determining the first impulse response width of described first Chebyshev window function, comprising: Obtain the target pulse width, the target sampling rate and the first peak-to-side lobe ratio; Based on the target pulse width, the target sampling rate, and the first peak-to-sidelobe ratio, the first Chebyshev window function is generated, and the first impulse response width is determined. 3. The method according to claim 1, wherein the determining a weight parameter, and modifying the edge point of the first Chebyshev window function based on the weight parameter to obtain a second Chebyshev window functions, including: The first Chebyshev window function is analyzed to obtain a first target point and a second target point; wherein, the edge point includes the first target point and the second target point; The position parameters of the first target point and the second target point are weighted based on each weight parameter to obtain a first weighted position parameter of the first target point and a second weighted value of the second target point. position parameter; The position parameter of the first target point of the first Chebyshev window function is updated based on the first weighted position parameter, and all the position parameters of the first Chebyshev window function are updated based on the second weighted position parameter. The position parameter of the second target point is obtained to obtain the second Chebyshev window function. 4. The method according to claim 3, characterized in that, determining the first time-frequency function based on the second Chebyshev window function, comprising: Determine the target bandwidth; Based on the target bandwidth, a stationary phase principle algorithm is used to process each of the second Chebyshev window functions to obtain a plurality of the first time-frequency functions. 5. The method according to claim 1, wherein the determining a target signal based on the first time-frequency function and the first impulse response width comprises: processing each of the first time-frequency functions to determine a plurality of first signals; determining a second peak-to-side lobe ratio and a second impulse response width for each of the first signals; The target signal is determined from a plurality of the first signals based on the first impulse response width, the second peak-to-side lobe ratio, and the second impulse response width. 6. The method according to claim 5, wherein the processing each of the first time-frequency functions to determine a plurality of first signals comprises: Integrating each of the first time-frequency functions to obtain the plurality of first signals. 7. The method according to claim 5, wherein the processing each of the first time-frequency functions to determine a plurality of first signals comprises: Modifying each of the first time-frequency functions to obtain a plurality of second time-frequency functions; The plurality of first signals are obtained by integrating each second time-frequency function. 8. The method according to claim 7, wherein the modifying each of the first time-frequency functions to obtain a plurality of the second time-frequency functions, comprising: Each first time-frequency function is analyzed to determine the position parameter of the connection point; wherein, the connection point is between the straight line corresponding to the linear function and the curve corresponding to the nonlinear function in the first time-frequency function. Junction; determining an expression for the linear function in each of the first time-frequency functions; Based on the expression of the linear function and the position parameter of the connection point, the position parameter of each point of the first time-frequency function is modified to obtain a plurality of second time-frequency functions. 9 . The method according to claim 8 , wherein, based on the expression of the linear function and the position parameter of the connection point, the position parameter of each point of the first time-frequency function is performed. 10 . Modified to obtain multiple second time-frequency functions, including: Determine the position parameter of the third target point based on the position parameter of the connection point and the expression; Based on the first position parameter of the connection point and the first position parameter of the third target point, the first position parameter of the fourth target point is determined from the points of the nonlinear function; wherein the position parameter includes the first position parameter and the second position parameter; Based on the expression and the first position parameter of the fourth target point, an updated second position parameter of the fourth target point is determined, and the updated position parameter is used to replace the description in the first time-frequency function The second position parameter of the fourth target point is obtained to obtain the plurality of second time-frequency functions. 10. The method of claim 5, wherein based on the first impulse response width, the second peak-to-side lobe ratio and the second impulse response width, from a plurality of the first impulse response widths The target signal is determined from the signal, including: determining a third impulse response width not greater than the first impulse response width from a plurality of second impulse response widths; determining a second signal from the first signal based on the third impulse response width; The target signal is obtained by determining the signal with the smallest second peak-to-side lobe ratio from the second signal. 11. A signal processing device, characterized in that the device comprises: a processor, a memory and a communication bus; The communication bus is used to realize the communication connection between the processor and the memory; The processor is used to execute the signal processing program in the memory to realize the following steps: generating a first Chebyshev window function, and determining a first impulse response width of the first Chebyshev window function; determining a weight parameter, and modifying the edge point of the first Chebyshev window function based on the weight parameter to obtain a second Chebyshev window function; determining a first time-frequency function based on the second Chebyshev window function; A target signal is determined based on the first time-frequency function and the first impulse response width. 12. A computer-readable storage medium, characterized in that, the computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to realize the claim The steps of the signal processing method of any one of claims 1 to 10.

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