CN114779182A - A time-domain sliding window three-dimensional multi-channel joint clutter suppression method based on FDA-MIMO radar - Google Patents

Abstract

The invention discloses a time domain sliding window three-dimensional multi-channel combined clutter suppression method based on FDA-MIMO radar, which comprises the following steps: transmitting K +2 pulses in a coherent processing interval, wherein the received echo data comprises data of L distance units; preprocessing echo data to obtain pulse data; respectively carrying out non-sliding, 1-time window sliding and 2-time window sliding on the pulse data which is received by the nth receiving channel and transmitted by the mth transmitting channel to obtain corresponding data; arranging all data into an overall vector; after time domain Doppler filtering is carried out on the total vector, the output of three adjacent Doppler channels is selected to be combined with a transmitting domain and a receiving domain to obtain a data vector; obtaining a secondary covariance matrix according to the data vector; obtaining the optimal weight vector after dimension reduction processing; and carrying out self-adaptive filtering processing on the preprocessed pulse data of each distance unit to obtain an output result. The method reduces the dimension, improves the robustness to errors, effectively inhibits clutter, and improves the Doppler frequency range of a detected target.

Description

A time-domain sliding window three-dimensional multi-channel joint clutter suppression method based on FDA-MIMO radar

technical field

The invention belongs to the technical field of radar signal processing, in particular to a time-domain sliding window three-dimensional multi-channel joint clutter suppression method based on FDA-MIMO radar.

Background technique

When the airborne early warning radar detects moving targets on the ground, it is in downward-looking operation. At this time, the radar faces strong ground clutter interference, and the moving targets may be submerged in the clutter. It is necessary to carry out clutter suppression processing. FDA-MIMO radar introduces the range-dimensional degree of freedom in the transmitting domain, which can separate clutter in different fuzzy areas and perform three-dimensional adaptive signal processing. The three-dimensional adaptive processing increases the emission dimension, and more sample data satisfying the condition of independent and identical distribution is needed when estimating the covariance matrix, so it is necessary to perform dimensionality reduction processing. At the same time, considering the existence of errors, a more robust processing method is also required.

The three-dimensional local joint dimensionality reduction processing method selects appropriate three-dimensional beams by joint transmit-receive two-dimensional spatial beamforming through Doppler filters, so as to realize the dimensionality reduction processing of the received data, and finally, the dimensionality reduction of multiple three-dimensional beams is processed. The data is subjected to three-dimensional adaptive processing to achieve clutter suppression while reducing the number of samples required.

Although the 3D local joint processing method has good performance under ideal conditions, the performance of this method decreases when there are channel amplitude and phase errors.

SUMMARY OF THE INVENTION

In order to solve the above problems existing in the prior art, the present invention provides a time-domain sliding window three-dimensional multi-channel joint clutter suppression method based on FDA-MIMO radar. The technical problem to be solved by the present invention is realized by the following technical solutions:

A time-domain sliding window three-dimensional multi-channel joint clutter suppression method based on FDA-MIMO radar, the clutter suppression method includes:

Step 1. M transmitting array elements transmit K+2 pulses within the coherent processing interval, and the echo data received by each receiving array element includes data of L distance units, wherein the FDA-MIMO radar includes M transmitting array elements and N receiving array elements;

Step 2, performing down-conversion, AD conversion, matched filtering and Bulter multi-beam preprocessing on the echo data in sequence to obtain preprocessed pulse data;

数据

和数据

其中，所述数据

包括第n个接收通道接收到经第m个发射通道发射的预处理后的第1个脉冲数据至第K个脉冲数据，所述数据

表示第n个接收通道接收到经第m个发射通道发射的预处理后的第2个脉冲数据至第K+1个脉冲数据，所述数据

表示第n个接收通道接收到经第m个发射通道发射的预处理后的第3个脉冲数据至第K+2个脉冲数据，0<l≤L，0<m≤M，0<n≤N；Step 3. For the l-th distance unit, the pre-processed pulse data received by the n-th receiving channel and transmitted by the m-th transmitting channel are processed respectively without sliding, sliding a window and sliding a window twice, and correspondingly obtains: data

data

and data

wherein the data

Including the nth receiving channel receiving the preprocessed 1st pulse data to the Kth pulse data transmitted by the mth transmitting channel, the data

Indicates that the nth receiving channel receives the preprocessed 2nd pulse data to the K+1th pulse data transmitted by the mth transmitting channel, the data

Indicates that the nth receiving channel receives the preprocessed 3rd pulse data to the K+2th pulse data transmitted by the mth transmitting channel, 0<l≤L, 0<m≤M, 0<n≤ N;

所述数据

和所述数据

排成总矢量；Step 4. Put all said data

the data

and the data

Arrange the total vector;

Step 5, for the l-th distance unit, after performing time-domain Doppler filtering on the total vector, select the output joint transmission domain and receiving domain of the adjacent three Doppler channels to obtain a data vector.

得到二次协方差矩阵R_TD；Step 6. According to the data vector

Get the quadratic covariance matrix R _TD ;

Step 7. Based on the quadratic covariance matrix R _TD and the total steering vector s _TD , the weight vector w is obtained according to the linearly constrained minimum variance criterion, and the total steering vector s _TD is steered through the transmitting steering vector, the receiving steering vector and the time domain steering vector get;

Step 8, obtaining the optimal weight vector w _TD of the weight vector w after dimensionality reduction processing;

Step 9: Based on the optimal weight vector w _TD , perform adaptive filtering processing on the preprocessed pulse data of each distance unit to obtain an output result z after clutter suppression.

In an embodiment of the present invention, the total vector is:

Among them, (·) ^T represents the matrix transpose operation, 0<m≤M, 0<n≤N.

In an embodiment of the present invention, the step 5 includes:

Step 5.1, for the lth distance unit, after performing time-domain Doppler filtering on the total vector, select the output of three adjacent Doppler channels, and the output is:

Wherein, w _tq are the time domain weights added by the kth, k-1, and k+1 Doppler channels respectively, Ι _MN is the identity matrix of MN × MN, ( ) ^H represents the matrix conjugate transpose operation;

所述数据矢量

为：Step 5.2. Rearrange the output into a data vector

the data vector

for:

In an embodiment of the present invention, the quadratic covariance matrix R _TD is:

where E[ ] represents the mathematical expectation.

In an embodiment of the present invention, the total steering vector s _TD is:

w_tk-1、w_tk、w_tk+1分别为第k-1、k、k+1个多普勒通道所加的时域权，(·)^H表示矩阵共轭转置运算。where s _T (f _T ) represents the transmit steering vector, f _T represents the transmit frequency, s _R (f _R ) represents the receive steering vector, f _R represents the receive frequency, s ₁ (f _dk ) represents the time domain steering vector, and f _dk represents the time-domain normalized frequency, s ₂ =[1, D ₁ , D ₂ ] ^T ,

w _tk-1 , w _tk , and w _tk+1 are the time domain weights added by the k-1, k, and k+1 th Doppler channels, respectively, (·) ^H represents the matrix conjugate transpose operation.

In an embodiment of the present invention, the method for obtaining the weight vector w is:

Among them, s.t. represents constraints.

In an embodiment of the present invention, the optimal weight vector w _TD is:

Among them, s _TD represents the total steering vector, and RT _TD represents the quadratic covariance matrix.

In an embodiment of the present invention, the output result z is:

Wherein, x _l represents the preprocessed pulse data of each distance unit.

Beneficial effects of the present invention:

In order to solve the problem of the large number of samples required for full-dimensional processing, the purpose of the present invention is to propose a three-dimensional multi-channel joint range ambiguity clutter suppression method based on time domain sliding window, which can be used for FDA-MIMO system radar and can separate ambiguity clutter at different distances. , the method improves the robustness of the error while reducing the dimension, effectively suppresses the clutter, and improves the Doppler frequency range of the detectable moving target.

Description of drawings

1 is a schematic flowchart of a time-domain sliding window three-dimensional multi-channel joint clutter suppression method based on FDA-MIMO radar provided by an embodiment of the present invention;

2 is a schematic diagram of a three-dimensional multi-channel joint distance fuzzy clutter suppression method based on a time-domain sliding window provided by an embodiment of the present invention;

3 is an output curve diagram provided by an embodiment of the present invention;

FIG. 4 is a performance curve diagram of an output signal-to-noise ratio loss provided by an embodiment of the present invention.

Detailed ways

The present invention will be described in further detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

Example 1

Please refer to FIG. 1 and FIG. 2. FIG. 1 is a schematic flowchart of a time-domain sliding window three-dimensional multi-channel joint clutter suppression method based on FDA-MIMO radar provided by an embodiment of the present invention, and FIG. 2 is provided by an embodiment of the present invention. A schematic diagram of a three-dimensional multi-channel joint range fuzzy clutter suppression method based on time-domain sliding windows. The embodiment of the present invention provides a time-domain sliding window three-dimensional multi-channel joint clutter suppression method based on FDA-MIMO radar, and the clutter suppression method includes:

Step 1. M transmitting array elements transmit K+2 pulses within the coherent processing interval, and the echo data received by each receiving array element includes data of L distance units, wherein the FDA-MIMO radar includes M transmitting array elements and N receiving array elements.

In this embodiment, the FDA-MIMO radar is a side-view FDA-MIMO radar.

Step 2. Perform down-conversion, AD conversion, matched filtering and Bulter multi-beam preprocessing on the echo data in sequence to obtain preprocessed pulse data.

In this embodiment, down-conversion is to down-convert a radio frequency signal to an intermediate frequency signal, AD conversion is to convert an analog signal to a digital signal, matched filtering is to realize pulse pressure and separate signals corresponding to different transmit waveforms, and Bulter multi-beam is to convert an analog signal into a digital signal. The multiple Fourier fundamental beams obtained are processed.

数据

和数据

其中，数据

包括第n个接收通道接收到经第m个发射通道发射的预处理后的第1个脉冲数据至第K个脉冲数据，数据

表示第n个接收通道接收到经第m个发射通道发射的预处理后的第2个脉冲数据至第K+1个脉冲数据，数据

表示第n个接收通道接收到经第m个发射通道发射的预处理后的第3个脉冲数据至第K+2个脉冲数据，0<l≤L，0<m≤M，0<n≤N。Step 3. For the l-th distance unit, the pre-processed pulse data received by the n-th receiving channel and transmitted by the m-th transmitting channel are processed respectively without sliding, sliding a window and sliding a window twice, and correspondingly obtains: data

data

and data

Among them, the data

Including the nth receiving channel receiving the preprocessed first pulse data to the Kth pulse data transmitted by the mth transmitting channel, the data

Indicates that the nth receiving channel receives the preprocessed 2nd pulse data to the K+1th pulse data transmitted by the mth transmitting channel, and the data

Indicates that the nth receiving channel receives the preprocessed 3rd pulse data to the K+2th pulse data transmitted by the mth transmitting channel, 0<l≤L, 0<m≤M, 0<n≤ N.

In this embodiment, sliding window processing is performed on the pulse data of each transmit channel and receive channel in the time domain.

数据

和数据

得到总矢量。Step 4. According to all data

data

and data

to get the total vector.

Specifically, the total vector formed by the data of these M×N channels is expressed as:

Among them, (·) ^T represents the matrix transpose operation, 0<m≤M, 0<n≤N.

Step 5. For the l-th distance unit, after performing time-domain Doppler filtering (DFT) on the total vector, select the output joint transmit domain and receive domain of the adjacent three Doppler channels to obtain a data vector.

In a specific embodiment, step 5 may specifically include:

和

即输出为：Step 5.1, for the l-th distance unit, after performing time-domain Doppler filtering on the total vector, select the outputs of three adjacent Doppler channels, which are respectively:

and

i.e. the output is:

Among them, w _tq are the time domain weights added by the k, k-1, and k+1 Doppler channels, respectively, Ι _MN is the identity matrix of MN × MN, and (·) ^H represents the matrix conjugate transpose operation.

数据矢量

为：Step 5.2. Rearrange the output into a data vector

data vector

for:

得到二次协方差矩阵R_TD，二次协方差矩阵R_TD为：Step 6. According to the data vector

The quadratic covariance matrix R _TD is obtained, and the quadratic covariance matrix R _TD is:

where E[ ] represents the mathematical expectation. In actual processing, sample data of adjacent distance units are often used for estimation.

Step 7: Based on the quadratic covariance matrix R _TD and the total steering vector s _TD , the weight vector w is obtained according to the linear constrained minimum variance criterion, and the total steering vector s _TD is obtained by the transmitting steering vector, the receiving steering vector and the time domain steering vector.

First, construct the total steering vector s _TD of the target to be detected, and the total steering vector s _TD is:

w_tk-1、w_tk、w_tk+1分别为第k-1、k、k+1个多普勒通道所加的时域权，(·)^H表示矩阵共轭转置运算。where s _T (f _T ) represents the transmit steering vector, f _T represents the transmit frequency, s _R (f _R ) represents the receive steering vector, f _R represents the receive frequency, s ₁ (f _dk ) represents the time domain steering vector, and f _dk represents the time-domain normalized frequency, s ₂ =[1, D ₁ , D ₂ ] ^T ,

w _tk-1 , w _tk , and w _tk+1 are the time domain weights added by the k-1, k, and k+1 th Doppler channels, respectively, (·) ^H represents the matrix conjugate transpose operation.

After that, the weight vector w is obtained by using the linearly constrained minimum variance criterion, and the calculation method of the weight vector w can be expressed as the following optimization problem:

Among them, s.t. represents constraints.

Step 8. Obtain the optimal weight vector w _TD of the weight vector w after the dimension reduction process, and the optimal weight vector w _TD is:

Among them, s _TD represents the total steering vector, and RT _TD represents the quadratic covariance matrix.

Step 9. Based on the optimal weight vector w _TD , perform adaptive filtering on the preprocessed pulse data of each distance unit to obtain an output result z after clutter suppression, and the output result z is:

Wherein, x _l represents the preprocessed pulse data of each distance unit.

The clutter suppression method proposed by the present invention is used for FDA-MIMO radar, adopts time domain sliding window processing, reduces the clutter freedom degree of each Doppler channel, and selects three Doppler channels to improve time domain clutter suppression It also reduces the pressure on the transmitter and receiver, which is beneficial to the suppression of fuzzy clutter and improves the detection performance.

Simulation experiments can further prove the beneficial effects of the present invention.

The equidistant linear array is used for both transmitting and receiving in the simulation experiment. The number of array elements is 6, the spacing between array elements is half wavelength, the number of coherent processing pulses is 10, the carrier frequency of the first transmitting array element is 1 GHz, and the frequency increment between array elements is 1.5KHz, 300 range units are selected, the pulse repetition frequency is 6KHz, the range ambiguity is 4, the platform speed is 200m/s, the beam direction is 90°, and the target slant range is 10km.

Simulation content 1: Under the above simulation parameters, considering 4% of the array element amplitude and phase error and clutter fluctuations, the output after dimensionality reduction adaptive processing is simulated, as shown in Figure 3. It can be clearly seen that the clutter suppression effect without sliding window processing is not as good as that of the method proposed in the present invention.

Simulation content 2: Under the above simulation parameters, considering 4% of the array element amplitude and phase error and clutter fluctuations, the output SNR loss after dimensionality reduction adaptive processing is simulated, and the three-dimensional local joint processing ( JDL) method was compared, as shown in Figure 4. The error causes a widening of the performance notch. The proposed method increases the number of samples through sliding window processing, and has a greater performance improvement than the JDL method.

In the description of this specification, description with reference to the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples", etc., mean specific features described in connection with the embodiment or example , structure, material or feature is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, those skilled in the art may combine and combine the different embodiments or examples described in this specification.

Although the application is described herein in conjunction with the various embodiments, those skilled in the art will understand and understand, by reviewing the drawings, the disclosure, and the appended claims, in practicing the claimed application. Other variations of the disclosed embodiments are implemented. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that these measures cannot be combined to advantage.

The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and it cannot be considered that the specific implementation of the present invention is limited to these descriptions. For those of ordinary skill in the technical field of the present invention, without departing from the concept of the present invention, some simple deductions or substitutions can be made, which should be regarded as belonging to the protection scope of the present invention.

Claims (8)

1. A time domain sliding window three-dimensional multi-channel combined clutter suppression method based on FDA-MIMO radar is characterized by comprising the following steps:

step 1, M transmitting array elements transmit K +2 pulses in a coherent processing interval, echo data received by each receiving array element comprises data of L distance units, wherein the FDA-MIMO radar comprises M transmitting array elements and N receiving array elements;

step 2, performing down-conversion, AD conversion, matched filtering and Bulter multi-beam preprocessing on the echo data in sequence to obtain preprocessed pulse data;

and 3, aiming at the l distance unit, respectively performing non-sliding, 1-time window sliding and 2-time window sliding on the pulse data which is received by the nth receiving channel and transmitted by the mth transmitting channel after preprocessing, and correspondingly obtaining data

Data of

And data

Wherein the data

The method comprises the steps that the nth receiving channel receives the preprocessed 1 st pulse data to the Kth pulse data transmitted by the mth transmitting channel, and the data

Indicating that the nth receiving channel receives the preprocessed 2 nd to K +1 th pulse data transmitted by the mth transmitting channel

Indicating that the nth receiving channel receives the preprocessed 3 rd pulse data to K +2 th pulse data transmitted by the mth transmitting channel, 0<l≤L，0<m≤M，0<n≤N；

Step 4, all the data are processed

The data

And said data

Arranging a total vector;

step 5, aiming at the first distance unit, after the time domain Doppler filtering is carried out on the total vector, the output joint transmitting domain and the receiving domain of three adjacent Doppler channels are selected to obtain a data vector

Step 6, according to the data vector

Obtaining a quadratic covariance matrix R_TD；

Step 7, based on the quadratic covariance matrix R_TDAnd the total steering vector s_TDObtaining a weight vector w according to a linear constraint minimum variance criterion, and obtaining a total guide vector s_TDThe method comprises the steps of obtaining a transmitting steering vector, a receiving steering vector and a time domain steering vector;

step 8, obtaining the optimal weight vector w of the weight vector w after the dimension reduction treatment_TD；

Step 9, based on the optimal weight vector w_TDAnd performing self-adaptive filtering processing on the preprocessed pulse data of each distance unit to obtain an output result z after clutter suppression.

2. The FDA-MIMO radar-based time domain sliding window three-dimensional multi-channel joint clutter suppression method according to claim 1, wherein the total vector is:

wherein, (.)^TDenotes a matrix transposition operation, 0<m≤M，0<n≤N。

3. The FDA-MIMO radar-based time domain sliding window three-dimensional multi-channel joint clutter suppression method according to claim 2, wherein the step 5 comprises:

step 5.1, aiming at the ith distance unit, after time domain Doppler filtering is carried out on the total vector, the outputs of three adjacent Doppler channels are selected, wherein the outputs are as follows:

wherein w_tqTime domain weights I added for the kth, k-1 and k +1 Doppler channels respectively_MNIs a unit matrix of MN × MN (·)^HRepresenting a matrix conjugate transpose operation;

step 5.2, rearranging the output into data vectors

The data vector

Comprises the following steps:

4. the FDA-MIMO radar-based time-domain sliding window three-dimensional multi-channel joint clutter suppression method of claim 1, wherein the quadratic covariance matrix R_TDComprises the following steps:

wherein E [. cndot. ] represents a mathematical expectation.

5. The FDA-MIMO radar-based time-domain sliding-window three-dimensional multi-channel joint clutter suppression method according to claim 1, wherein the total steering vector s_TDComprises the following steps:

wherein s is_T(f_T) Representing a transmit steering vector, f_TRepresenting the transmission frequency, s_R(f_R) Representing the received steering vector, f_RRepresenting received frequencyRate, s₁(f_dk) Representing time-domain steering vectors, f_dkRepresenting the normalized frequency, s, of the time domain₂＝[1,D₁,D₂]^T，

w_tk-1、w_tk、w_tk+1Time domain weights added to the k-1, k +1 Doppler channels, respectively, (.)^HRepresenting a matrix conjugate transpose operation.

6. The FDA-MIMO radar-based time domain sliding window three-dimensional multi-channel joint clutter suppression method according to claim 1, wherein the weight vector w is obtained by:

wherein s.t. represents a constraint.

7. The FDA-MIMO radar-based time-domain sliding window three-dimensional multi-channel joint clutter suppression method according to claim 1, wherein the optimal weight vector w_TDComprises the following steps:

wherein s is_TDDenotes the total steering vector, R_TDRepresenting a quadratic covariance matrix.

8. The FDA-MIMO radar-based time domain sliding window three-dimensional multi-channel joint clutter suppression method according to claim 7, wherein the output result z is:

wherein x is_lRepresenting the preprocessed pulse data for each range bin.

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