LFM signal adaptive non-uniform segmented frequency domain pulse compression implementation method

Abstract

The application discloses an adaptive non-uniform segmented frequency domain pulse compression implementation method of an LFM signal. The method adopts an overlap reservation method, performs frequency domain pulse compression adaptive segmentation based on radar echo data length and signal parameters, then performs frequency domain pulse compression on each segment according to the segmentation parameters, and finally obtains the final pulse compression result by intercepting and splicing the processing result of each segment to realize frequency domain pulse compression processing. Under the premise of ensuring the correctness of the pulse compression processing result, the application can greatly reduce the time delay of CPU pulse compression processing under certain conditions, reduces the use of CPU resources, and can be widely applied to pulse compression system radars.

Description

Technical Field

[0001] This invention belongs to the field of pulse compression technology in radar signal processing, and specifically relates to a method for implementing adaptive non-uniform segmented frequency domain pulse compression of LFM signals. Background Technology

[0002] Currently, radar pulse compression processing employs digital signal processing. Large time-bandwidth product signals are typically implemented in the frequency domain using FFT. In the specific implementation of frequency domain pulse compression methods, the number of FFT / IFFT points is not arbitrarily chosen; usually, a power of 2 corresponds to a value greater than or equal to the data length and signal length minus one. Therefore, zero-padding is necessary before performing FFT on the coefficients and input signal. However, under certain conditions, the length of the zero-padding data significantly increases the computational load and processing delay. A common solution is equally spaced segmented frequency domain pulse compression. Segmentation requires repeated calculations, so the more segments there are, the greater the increase in data volume and CPU processing resources. Without segmentation, unnecessary computations waste computational resources. Therefore, an adaptive non-uniform segmented frequency domain pulse compression method for LFM signals is proposed, which significantly reduces the computational delay of the pulse compression algorithm while maximizing computational efficiency. Summary of the Invention

[0003] The purpose of this invention is to solve the problems mentioned in the background art. Based on data and signal parameters, adaptive segmented frequency domain pulse compression processing of radar echo data is performed. By truncating and splicing the segmented frequency domain pulse compression results, adaptive non-uniform segmented frequency domain pulse compression of LFM signals is achieved.

[0004] To achieve the objective of this invention, a method for implementing adaptive non-uniform segmented frequency domain pulse compression of LFM signals is disclosed, comprising the following steps:

[0005] Step 1: Determine the echo data length Num_Data and signal length NumT_Sig based on the LFM signal's time width T, data sampling period PRT, and sampling frequency Fs.

[0006] Step 2: Determine the number of points NumFFT for a single frequency domain pulse compression FFT based on the echo data length Num_Data and the signal length NumT_Sig;

[0007] Step 3: Calculate the number of FFT points NumFFT_Seg for each segment of the adaptive segmented frequency domain pulse compression, the segment data length DataLen_Seg, and the segment data start data DataIndex_Seg parameter.

[0008] Step 4: Pad the end of the segmented data with zeros to the length of the segment FFT points NumFFT_Seg according to the frequency domain pulse compression processing method, and perform frequency domain pulse compression processing on each segment separately.

[0009] Step 5: Based on the data start and data length parameters of each segment, the frequency domain pulse compression processing results of each segment are truncated and spliced ​​to realize the adaptive non-uniform segmented frequency domain pulse compression of LFM signal.

[0010] Furthermore, in step 1, the echo data length Num_Data is calculated as Num_Data = PRT * Fs, and the signal length NumT_Sig is calculated as NumT_Sig = T * Fs.

[0011] Further, in step 2, based on the data length Num_Data and signal length NumT_Sig parameters, the power of 2 is taken to be greater than or equal to Num_Data + NumT_Sig-1 to determine the number of points NumFFT in the frequency domain pulse compression FFT, i.e., NumFFT = 2^m ≧ Num_Data + NumT_Sig-1.

[0012] Further, in step 3, the calculation method for the number of FFT points NumFFT_Seg in each segment is as follows: the number of FFT points in the adaptive segmented frequency domain pulse compression is calculated based on the calculated number of FFT points NumFFT, data length Num_Data, and signal length NumT_Sig parameters, to obtain the number of FFT points in the first segment NumFFT_Seg1 = NumFFT / 2, and the number of FFT points in the second segment NumFFT_Seg2 = 2^ceil(log2(Num_Data-DataLen_Seg1+2*NumT_Sig-1)), where DataLen_Seg1 is the data length of the first segment.

[0013] Further, in step 3, the calculation method for the segmented data length DataLen_Seg and the segment start parameter is as follows: the adaptive segmented frequency domain pulse compression data length and data start parameter are calculated based on the calculated first frequency domain pulse compression FFT point number NumFFT, data length Num_Data, and signal length NumT_Sig parameters. The first segment data starts with DataIndex_Seg1 = 1, and the first segment data length DataLen_Seg1 = NumFFT_Seg1 - NumT_Sig; the second segment data starts with DataIndex_Seg2 = DataLen_Seg1 - NumT_Sig + 2, and the second segment data length DataLen_Seg2 = Num_Data - DataLen_Seg1 + NumT_Sig - 1.

[0014] Furthermore, in step 4, the frequency domain pulse compression processing method specifically includes the following steps:

[0015] Step 4-1: Determine the weight coefficients of the digital pulse compression filter h(n) = exp(-i*pi*B / T*t_ref.^2) based on the basic parameters of the signal, including the signal bandwidth B, time width T, and sampling rate Fs, where i represents the imaginary unit, pi represents pi, t_ref = -T / 2:dt:T / 2-dt, and dt = 1 / Fs;

[0016] Step 4-2: Extract the original data according to the segment start and segment length parameters, and pad the extracted data with zeros to the length of the segment FFT points NumFFT_Seg, forming the data to be processed Data_SegN_tmp;

[0017] Step 4-3: Perform NumFFT_Seg point FFT on Data_SegN_tmp and h(n) respectively to obtain the data frequency domain response Data_SegN_FFT and the filter frequency domain response H_N, where Data_SegN_FFT = FFT(Data_SegN_tmp, NumFFT_Seg) and H_N = FFT(h(n), NumFFT_Seg).

[0018] Step 4-4: Perform IFFT on the result of multiplying Data_SegN_FFT and H_N to obtain the segmented pulse compression result y_N, y_N = IFFT(Data_SegN_FFT*H_N).

[0019] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The steps of the processor executing the computer program are as follows: to implement a method for adaptive non-uniform segmented frequency domain pulse compression of an LFM signal.

[0020] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of an adaptive non-uniform segmented frequency domain pulse compression method for LFM signals.

[0021] Compared with the prior art, the significant advancements of this invention are: 1) the use of frequency domain pulse compression and existing fast Fourier transform algorithms greatly improves the efficiency of digital pulse compression; 2) the adaptive non-uniform segmentation method under certain conditions can greatly reduce the computational delay of the pulse compression algorithm while maximizing computational efficiency; 3) the adaptive non-uniform segmentation method has flexibility and wide applicability to various signal forms.

[0022] To more clearly illustrate the functional characteristics and structural parameters of the present invention, further explanation is provided below in conjunction with the accompanying drawings and specific embodiments. Attached Figure Description

[0023] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0024] Figure 1 A schematic diagram of the implementation process of adaptive non-uniform segmented frequency domain pulse compression for LFM signals;

[0025] Figure 2 Schematic diagram of adaptive non-uniform segmentation;

[0026] Figure 3 Schematic diagram of simulated LFM radar echo signal generation;

[0027] Figure 4 Schematic diagram of post-processing results of segmented pulse compression;

[0028] Figure 5 A schematic diagram comparing the results of single pulse pressure and segmented pulse pressure processing;

[0029] Figure 6 A schematic diagram of the amplitude error between single pulse pressure and segmented pulse pressure processing results. Detailed Implementation

[0030] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] like Figure 1 As shown, a method for implementing adaptive non-uniform segmented frequency domain pulse compression of LFM signals includes the following steps:

[0032] Step 1: Determine the signal length NumT_Sig = T*Fs, the data length Num_Data = PRT*Fs, and the number of FFT points in one frequency domain pulse compression NumFFT = 2^m≧Num_Data+NumT_Sig-1 based on the LFM signal's time width T, data sampling period PRT, and sampling frequency Fs parameters.

[0033] Step 2: Using the overlap-preservation method, the number of points for the adaptive segmented frequency domain pulse compression FFT is calculated based on the calculated number of FFT points NumFFT, data length Num_Data, and signal length NumT_Sig: NumFFT_Seg1 = NumFFT / 2, NumFFT_Seg2 = 2^ceil(log2(Num_Data-DataLen_Seg1+2*NumT_Sig-1));

[0034] Step 3: Using the overlap-preservation method, the adaptive segmented frequency domain pulse compression data length and data start parameters are calculated based on the calculated FFT point number NumFFT parameter, data length Num_Data, and signal length NumT_Sig parameter: the data start is DataIndex_Seg1 = 1, and the data length is DataLen_Seg1 = NumFFT_Seg1 - NumT_Sig; the data start of the second segment is DataIndex_Seg2 = DataLen_Seg1 - NumT_Sig + 2, and the data length is DataLen_Seg2 = Num_Data - DataLen_Seg1 + NumT_Sig - 1;

[0035] Step 4: Determine the digital pulse compression filter coefficients h(n) = exp(-i*pi*B / T*t_ref.^2) based on the basic parameters of the signal, including signal bandwidth B, time width T, and sampling rate Fs, where i represents the imaginary unit, pi represents pi, t_ref = -T / 2:dt:T / 2-dt, dt = 1 / Fs; extract the original data according to the segmented calculation parameters, and pad the extracted data segments with zeros to the length NumFFT_SegN (N = 1 or 2) to form the data to be processed Data_SegN_tmp; process Data_ Perform a NumFFT_SegN-point FFT on SegN_tmp and h(n) to obtain the frequency domain responses Data_SegN_FFT and H_N, where Data_SegN_FFT = FFT(Data_SegN_tmp, NumFFT_SegN) and H_N = FFT(h(n), NumFFT_SegN). Finally, perform an IFFT on the result of multiplying Data_SegN_FFT and H_N to obtain the segmented pulse compression result y_N, where y_N = IFFT(Data_SegN_FFT * H_N).

[0036] Step 5: Extract and stitch the segmented pulse compression results to obtain the final processed result, Data_PC. The calculation formula is as follows:

[0037] Data_PC(DataIndex_Seg1:DataIndex_Seg1+DataLen_Seg1-1)

[0038] =y1(NumT_Sig+1:NumT_Sig+DataLen_Seg1);

[0039] Data_PC(DataIndex_Seg2:DataIndex_Seg2+DataLen_Seg2-1)=

[0040] y2(NumT_Sig+1:NumT_Sig+DataLen_Seg2).

[0041] Example

[0042] Simulation conditions:

[0043] The LFM echo signal of a single-pulse radar was generated using the MATLAB platform. The signal has a carrier frequency of 3 GHz, a bandwidth of 4 MHz, a sampling rate of 5 MHz, a pulse width of 20 μs, and a repetition period of 2000 μs. The echo contains information on three target points at distances of 214,800 meters, 244,800 meters, and 274,800 meters, with a signal-to-noise ratio of 60 dB for each. The echo signal is shown below. Figure 3 As shown.

[0044] Step 1: Determine the basic parameters of the signal. The signal length is NumT_Sig = 100, and the data length is Num_Data = 10000.

[0045] The number of points for a single frequency domain pulse compression FFT is NumFFT = 16384.

[0046] Steps 2 and 3: Combining Figure 2 Calculate the number of frequency domain pulse compression FFT points NumFFT_Seg1 and NumFFT_Seg2 for adaptive segmentation, as well as the start and end points of the segmented data truncation.

[0047] % First paragraph

[0048] NumFFT_Seg1 = 8192;

[0049] DataIndex_Seg1 = 1;

[0050] DataLen_Seg1 = 8092;

[0051] % Second paragraph

[0052] NumFFT_Seg2 = 4096;

[0053] DataIndex_Seg2 = 7994;

[0054] DataLen_Seg2 = 2007;

[0055] Step 4: Pad the data with zeros at the end and perform frequency domain pulse compression on each segment.

[0056] Step 5: Extract the pulse compression results and concatenate them according to the data start and length parameters of the segments to obtain the final processing result. Figure 4The simulation results of the three targets after segmented frequency domain pulse compression are shown. The target at the 8160 distance cell is located at the segmented position, so details are shown. The results show that the target pulse compression at the segment point is correct.

[0057] Figure 5 The display shows the amplitude results of simulation data for both non-segmented frequency domain pulse compression and adaptive segmented frequency domain pulse compression. Figure 6 The display shows the amplitude error between the non-segmented frequency domain pulse compression and the adaptive segmented frequency domain pulse compression results. By comparing the amplitude and error results, the non-segmented frequency domain pulse compression and the adaptive segmented frequency domain pulse compression results are completely identical, verifying the correctness of the proposed method for implementing adaptive segmented frequency domain pulse compression of LFM signals.

[0058] This invention, verified through MATLAB simulation and experimental data, demonstrates that, under certain conditions, computational efficiency can be improved by approximately 40% while reducing CPU resource usage, provided the accuracy of the pulse compression processing results is maintained. This method is not only applicable to radar LFM signals but also has broad applicability to other pulse compression radar signals.

[0059] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0060] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for implementing adaptive non-uniform segmented frequency domain pulse compression of LFM signals, characterized in that, Includes the following steps: Step 1: Determine the echo data length Num_Data and signal length NumT_Sig based on the LFM signal's time width T, data sampling period PRT, and sampling frequency Fs. Step 2: Determine the number of points NumFFT for a single frequency domain pulse compression FFT based on the echo data length Num_Data and the signal length NumT_Sig; Step 3: Calculate the number of FFT points NumFFT_Seg, segment data length DataLen_Seg, and segment data start DataIndex_Seg parameters for each segment of the adaptive segmented frequency domain pulse compression. Step 4: Pad the end of the segmented data with zeros to the length of the segment FFT points NumFFT_Seg according to the frequency domain pulse compression processing method, and perform frequency domain pulse compression processing on each segment separately. Step 5: Based on the data start and data length parameters of each segment, the frequency domain pulse compression processing results of each segment are truncated and spliced ​​to realize the adaptive non-uniform segmented frequency domain pulse compression of LFM signal.

2. The method for implementing adaptive non-uniform segmented frequency domain pulse compression of LFM signals according to claim 1, characterized in that, In step 1, the echo data length Num_Data is calculated as Num_Data = PRT * Fs, and the signal length NumT_Sig is calculated as NumT_Sig = T * Fs.

3. The method for implementing adaptive non-uniform segmented frequency domain pulse compression of LFM signals according to claim 1, characterized in that, In step 2, based on the data length Num_Data and signal length NumT_Sig parameters, the number of points NumFFT for a single frequency domain pulse compression FFT is determined by taking a power of 2 greater than or equal to Num_Data + NumT_Sig-1, i.e., NumFFT = 2^m ≧ Num_Data + NumT_Sig-1.

4. The method for implementing adaptive non-uniform segmented frequency domain pulse compression of LFM signals according to claim 1, characterized in that, In step 3, the calculation method for the number of FFT points NumFFT_Seg in each segment is as follows: the number of FFT points in the adaptive segmented frequency domain pulse compression FFT is calculated based on the calculated number of FFT points NumFFT, data length Num_Data, and signal length NumT_Sig parameters, to obtain the number of FFT points in the first segment NumFFT_Seg1 = NumFFT / 2, and the number of FFT points in the second segment NumFFT_Seg2 = 2^ceil(log2(Num_Data - DataLen_Seg1 +2*NumT_Sig-1)), where DataLen_Seg1 is the data length of the first segment.

5. The method for implementing adaptive non-uniform segmented frequency domain pulse compression of LFM signals according to claim 4, characterized in that, In step 3, the calculation method for the segmented data length DataLen_Seg and the segment start parameter is as follows: Based on the calculated number of FFT points NumFFT, data length Num_Data, and signal length NumT_Sig parameters, the adaptive segmented frequency domain pulse compression data length and data start parameter are calculated. The first segment data starts with DataIndex_Seg1 = 1, and the first segment data length DataLen_Seg1 = NumFFT_Seg1 - NumT_Sig; the second segment data starts with DataIndex_Seg2 = DataLen_Seg1 - NumT_Sig + 2, and the second segment data length DataLen_Seg2 = Num_Data - DataLen_Seg1 + NumT_Sig - 1.

6. The method for implementing adaptive non-uniform segmented frequency domain pulse compression of LFM signals according to claim 1, characterized in that, Step 4, the frequency domain pulse compression processing method specifically includes the following steps: Step 4-1: Determine the weight coefficients of the digital pulse compression filter h(n) = exp(-i*pi*B / T*t_ref.^2) based on the basic parameters of the signal, including the signal bandwidth B, time width T, and sampling rate Fs, where i represents the imaginary unit, pi represents pi, t_ref = -T / 2: dt : T / 2-dt, dt = 1 / Fs; Step 4-2: Extract the original data according to the segment start and segment length parameters, and pad the extracted data with zeros to the length of the segment FFT points NumFFT_Seg, forming the data to be processed Data_SegN_tmp; Step 4-3: Perform NumFFT_Seg point FFT on Data_SegN_tmp and h(n) respectively to obtain the data frequency domain response Data_SegN_FFT and the filter frequency domain response H_N, where Data_SegN_FFT = FFT(Data_SegN_tmp, NumFFT_Seg), H_N = FFT(h(n), NumFFT_Seg); Step 4-4: Perform IFFT on the result of multiplying Data_SegN_FFT and H_N to obtain the segmented pulse compression result y_N, y_N=IFFT(Data_SegN_FFT*H_N).

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 6.

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