CN113435313A - Pulse frequency domain feature extraction method based on DFT - Google Patents
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Abstract
本发明提供一种基于DFT的脉冲频域特征提取方法，包括如下步骤：步骤1，对于给定的脉冲进行粗分辨率的DFT变换得到功率频谱，并在功率频谱上求得粗略中心频率，并定义带宽；步骤2，基于步骤1求得的粗略中心频率，选择DFT变换需要的中心频率、分辨率和频率范围；步骤3，对于给定的脉冲，利用定义的带宽以及步骤2选择的中心频率、分辨率和频率范围进行DFT运算，得到需要的脉冲频域特征。本发明利用DFT可以在频域不受时长变化、能够改善信噪比等特性，解决提取脉冲频域特征时容易测不准，同时规避FFT变换在采样率、脉冲宽度等不同时容易引入加窗效应和频域对准等问题；并且还能够减小运算量和存储空间。
The present invention provides a DFT-based pulse frequency domain feature extraction method, which includes the following steps: Step 1: Perform a coarse-resolution DFT transformation on a given pulse to obtain a power spectrum, and obtain a rough center frequency on the power spectrum, and Define the bandwidth; step 2, based on the rough center frequency obtained in step 1, select the center frequency, resolution and frequency range required by the DFT transform; step 3, for a given pulse, use the defined bandwidth and the center frequency selected in step 2 , resolution and frequency range to perform DFT operation to obtain the required pulse frequency domain characteristics. By using DFT, the invention can not change the time length in the frequency domain, can improve the signal-to-noise ratio and other characteristics, solves the problem that it is easy to be inaccurate when extracting the pulse frequency domain characteristics, and avoids the easy introduction of windowing when the sampling rate and pulse width of the FFT transform are different. effects and frequency domain alignment; and can also reduce the amount of computation and storage space.
Description
Technical Field
The invention relates to the technical field of pulse feature extraction, in particular to a pulse frequency domain feature extraction method based on DFT (discrete Fourier transform).
Background
Many characteristics of pulse signals are reflected in a pulse modulation domain, so that the pulse signals have special significance for the identification of a radiation source, and are concerned about in the fields of signal detection, parameter estimation, target classification and the like.
The pulse contains rich non-linear characteristics, such as pulse width, rising and falling edges, overshoot, inflection point and the like. These characteristics are difficult to estimate accurately, and may vary with different signal-to-noise ratios, amplitudes, widths, etc. of the pulses, and at the same time, different digital sampling lengths of the obtained signals are also caused by different signal detection and sampling rates in practical applications. In general, when parameter estimation and target classification are performed, the characteristics of the desired signal are as invariant as possible to the dynamic factors, so that various processing for transforming the signal from the time domain to the frequency domain is a good choice.
Mapping a time domain signal to a frequency domain based on Fast Fourier Transform (FFT), and controlling the resolution of the frequency domain by adjusting the number of FFT points in ways of increasing interpolation, zero padding and the like, but the methods bring signal distortion or window effect and are difficult to be applied to occasions with higher requirements on signal characteristic precision; for pulse feature extraction, the influence of links such as signal feature time domain and frequency domain alignment, normalization and the like is reduced.
Disclosure of Invention
The invention aims to provide a pulse frequency domain feature extraction method based on DFT, so as to solve the technical problems.
The invention provides a pulse frequency domain feature extraction method based on DFT, which comprises the following steps:
and 3, for a given pulse, performing DFT operation by using the defined bandwidth and the central frequency, resolution and frequency range selected in the step 2 to obtain the required pulse frequency domain characteristic.
Further, the method for performing full-frequency-domain DFT with coarse resolution on the given pulse in step 1 to obtain the power spectrum includes: performing DFT of coarse resolution on a given pulse X to convert the pulse X into a whole frequency domain aliasing period corresponding to a sampling rate, so as to obtain a frequency domain characteristic X (omega) of the pulse X; the power spectrum of the frequency domain feature X (ω) is then calculated.
Further, the method for obtaining the coarse center frequency on the power spectrum in step 1 comprises: the coarse center frequency is obtained by calculating the centroid of the power spectrum.
Further, the bandwidth in step 1 is directly defined as the 3dB bandwidth.
Further, in step 3, normalization needs to be performed on a given pulse before performing DFT operation.
Further, the method for normalizing the given pulse includes peak normalization or time-domain envelope normalization.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. the method utilizes the characteristics that DFT can not be subjected to time length change in the frequency domain, can improve the signal-to-noise ratio and the like, solves the problems that inaccurate measurement is easy to carry out when pulse frequency domain characteristics are extracted, and simultaneously avoids the problems that windowing effect and frequency domain alignment are easy to introduce when FFT conversion is carried out at different sampling rates, pulse widths and the like.
2. The invention firstly utilizes the DFT of the coarse resolution to estimate the parameters of the pulse, thereby greatly saving the operation amount, being capable of adjusting the resolution and being more flexible in practical application.
3. The second DFT conversion is more targeted, only the frequency in the range with the pulse signal is operated, the storage space overhead and the operation resource overhead are reduced, the problem of time-frequency domain normalization brought by various factors in practical application can be solved, and the accuracy of image pulse frequency domain characteristics such as noise outside the pulse is reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart of a DFT-based pulse frequency domain feature extraction method according to an embodiment of the present invention.
FIG. 2 is a flowchart of step 1 of an embodiment of the present invention.
FIG. 3 is a flowchart of step 3 of the present invention
Fig. 4 is a comparison graph of the time domain characteristics of two simulation signals in the FFT.
FIG. 5 is a graph of DFT signature comparison of two simulated signals at a specified frequency range and resolution.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
As shown in fig. 1, this embodiment proposes a pulse frequency domain feature extraction method based on DFT, which includes the following steps:
As shown in fig. 2, step 1 includes:
(1) and performing full-frequency-domain DFT conversion of coarse resolution on a given pulse to obtain a power spectrum. Specifically, for a given pulse X, performing DFT conversion of coarse resolution to the entire frequency domain aliasing period corresponding to the sampling rate, thereby obtaining a frequency domain feature X (ω) of the pulse X; the power spectrum of the frequency domain feature X (ω) is then calculated.
(2) And obtaining the rough center frequency on the power spectrum, wherein the rough center frequency can be obtained by calculating the mass center of the power spectrum.
(3) The bandwidth is defined, which is typically defined as a 3dB bandwidth.
And 3, for a given pulse, performing DFT operation by using the defined bandwidth and the central frequency, resolution and frequency range selected in the step 2 to obtain the required pulse frequency domain characteristic.
As shown in fig. 3, step 3 includes:
(1) for normalization of a given pulse, peak normalization or time-domain envelope normalization may be generally employed.
(2) And (3) performing DFT operation by using the defined bandwidth and the central frequency, resolution and frequency range selected in the step (2) to obtain the required pulse frequency domain characteristics.
In order to prove the effectiveness of the pulse frequency domain feature extraction method based on the DFT, the pulse frequency domain feature extraction method based on the DFT is subjected to a simulation test and is processed according to the processing flows of step 1, step 2 and step 3 shown in fig. 1, fig. 2 and fig. 3. Firstly, performing DFT conversion of coarse resolution on a given pulse to obtain a power spectrum, obtaining a coarse center frequency on the power spectrum, and defining a bandwidth; then, based on the rough center frequency obtained in the step 1, selecting the center frequency, the resolution and the frequency range required by DFT conversion; and finally, for a given pulse, performing DFT operation by using the defined bandwidth and the central frequency, resolution and frequency range selected in the step 2 to obtain the required pulse frequency domain characteristic.
The two simulated pulse signals are chirp pulse signals with the frequency of 100MHz and 125MHz respectively, the pulse width of 1us and 2us respectively, the bandwidth of 1MHz, and the signal sampling frequency of 500 MHz. The digital sample lengths obtained for different signals are different at this time.
FIG. 4 is a comparison of the features of two simulated signals in the FFT time domain, which is difficult to compare and distinguish; in fig. 4, the abscissa is frequency, corresponding to the full frequency domain, and the ordinate is power.
FIG. 5 is a comparison of DFT characteristics of two simulated signals at a given frequency range and resolution, with the pulses of two different parameters having a clear distinction; in fig. 5, the abscissa is the designated frequency range after DFT conversion, the actual center frequencies of different pulses are different, and the ordinate is power.
Therefore, the pulse frequency domain feature extraction method based on DFT can realize high-precision pulse feature characterization under the condition of noise and background interference, and proves the effectiveness of the invention. And the invention has the following beneficial effects:
1. the method utilizes the characteristics that DFT can not be subjected to time length change in the frequency domain, can improve the signal-to-noise ratio and the like, solves the problems that inaccurate measurement is easy to carry out when pulse frequency domain characteristics are extracted, and simultaneously avoids the problems that windowing effect and frequency domain alignment are easy to introduce when FFT conversion is carried out at different sampling rates, pulse widths and the like.
2. The invention firstly utilizes the DFT of the coarse resolution to estimate the parameters of the pulse, thereby greatly saving the operation amount, being capable of adjusting the resolution and being more flexible in practical application.
3. The second DFT conversion is more targeted, only the frequency in the range with the pulse signal is operated, the storage space overhead and the operation resource overhead are reduced, the problem of time-frequency domain normalization brought by various factors in practical application can be solved, and the accuracy of image pulse frequency domain characteristics such as noise outside the pulse is reduced.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A pulse frequency domain feature extraction method based on DFT is characterized by comprising the following steps:
step 1, performing DFT (discrete Fourier transform) conversion of coarse resolution on a given pulse to obtain a power spectrum, obtaining a coarse center frequency on the power spectrum, and defining a bandwidth;
step 2, selecting the center frequency, resolution and frequency range required by DFT conversion based on the rough center frequency obtained in the step 1;
and 3, for a given pulse, performing DFT operation by using the defined bandwidth and the central frequency, resolution and frequency range selected in the step 2 to obtain the required pulse frequency domain characteristic.
2. The DFT-based pulse frequency domain feature extraction method as claimed in claim 1, wherein the step 1 of performing full-frequency domain DFT with coarse resolution on the given pulse to obtain the power spectrum comprises: performing DFT of coarse resolution on a given pulse X to convert the pulse X into a whole frequency domain aliasing period corresponding to a sampling rate, so as to obtain a frequency domain characteristic X (omega) of the pulse X; the power spectrum of the frequency domain feature X (ω) is then calculated.
3. The DFT-based pulse frequency domain feature extraction method as claimed in claim 1, wherein the method for obtaining the coarse center frequency on the power spectrum in step 1 comprises: the coarse center frequency is obtained by calculating the centroid of the power spectrum.
4. The DFT-based pulse frequency domain feature extraction method as recited in claim 1, wherein the bandwidth in step 1 is directly defined as a 3dB bandwidth.
5. The DFT-based pulse frequency domain feature extraction method as claimed in claim 1, wherein in step 3, normalization is performed on a given pulse before DFT operation is performed.
6. The DFT-based pulse frequency-domain feature extraction method of claim 5, wherein the method of normalizing a given pulse comprises peak normalization or time-domain envelope normalization.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1626549A2 (en) * | 2004-08-11 | 2006-02-15 | Rohde & Schwarz GmbH & Co. KG | Method and apparatus for estimating carrier frequency using a block-wise coarse estimation |
| CN103777199A (en) * | 2014-02-24 | 2014-05-07 | 中国科学院电子学研究所 | Distance measuring method of frequency modulated continuous wave radar system |
| CN107710323A (en) * | 2016-01-22 | 2018-02-16 | 弗劳恩霍夫应用研究促进协会 | Apparatus and method for encoding or decoding audio multi-channel signal using spectral domain resampling |
| CN108509377A (en) * | 2018-03-19 | 2018-09-07 | 东南大学 | A kind of pulse signal arrival time based on along feature extraction and pulsewidth method of estimation |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1626549A2 (en) * | 2004-08-11 | 2006-02-15 | Rohde & Schwarz GmbH & Co. KG | Method and apparatus for estimating carrier frequency using a block-wise coarse estimation |
| CN103777199A (en) * | 2014-02-24 | 2014-05-07 | 中国科学院电子学研究所 | Distance measuring method of frequency modulated continuous wave radar system |
| CN107710323A (en) * | 2016-01-22 | 2018-02-16 | 弗劳恩霍夫应用研究促进协会 | Apparatus and method for encoding or decoding audio multi-channel signal using spectral domain resampling |
| CN108509377A (en) * | 2018-03-19 | 2018-09-07 | 东南大学 | A kind of pulse signal arrival time based on along feature extraction and pulsewidth method of estimation |
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