Dense target coherent accumulation method based on adaptive filter
By using the dense target comparison accumulation method of adaptive filters in radar signal processing, the problem of poor performance of traditional methods when processing dense targets is solved, and higher data analysis accuracy is achieved.
Patent Information
- Application Number
- CN202510233247.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-28
- Publication Date
- 2025-06-06
AI Technical Summary
In the case of processing intensive targets, the traditional phase error compensation method has poor performance, resulting in defocusing problems in the Doppler dimension, affecting the accuracy of data analysis.
The dense target phase comparison accumulation method based on an adaptive filter is adopted, and the phase comparison accumulation of the dense target signal is achieved by pulse compression and equalizing the echo signal, and frequency filtering and phase compensation are used to perform frequency filtering and phase compensation.
It effectively avoids the omission of weak target signals, reduces the probability of defocusing in the Doppler dimension, and improves the accuracy of data analysis.
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Figure CN120103291A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a dense target coherent accumulation method based on an adaptive filter. Background Art
[0002] Radar systems are often used to detect, locate and track low-altitude targets. Specifically, the radar emitter transmits radar signals, receives reflected radar signals, and performs data analysis on the received radar signals to determine the detected targets and target types. Affected by airflow interference and flight trajectory, the received radar signals are usually mixed with signals returned by multiple targets, which can easily cause defocusing in the Doppler dimension when performing data analysis. To address this problem, the existing processing method is to perform phase compensation on the received radar signal. However, the traditional phase error compensation method only performs well when processing a single signal, and its performance is greatly reduced when processing dense targets. Therefore, it is urgent to provide a coherent accumulation method for multi-target signals to solve the above problems. Summary of the invention
[0003] In order to solve the above problems existing in the prior art, the present invention provides a dense target coherent accumulation method based on an adaptive filter. The technical problem to be solved by the present invention is achieved by the following technical solutions:
[0004] The present invention provides a dense target coherent accumulation method based on an adaptive filter, comprising: performing pulse compression processing on an acquired echo signal containing multiple targets in a distance dimension to obtain a group of compressed signals; using a distance resolution, evenly dividing a signal sequence of the compressed signal in the distance dimension to obtain I groups of signals to be filtered, where I is a positive integer greater than or equal to 1; using an adaptive filtering function corresponding to the i-th group of signals to be filtered, performing frequency filtering on the i-th group of signals to be filtered, and extracting an i-th filtered signal, where i is less than or equal to I; performing phase compensation processing on the i-th filtered signal in an azimuth dimension to obtain an i-th phase compensated signal, and continuing to process the i+1-th group of signals to be filtered to obtain an i+1-th phase compensated signal, until an i-th phase compensated signal is obtained; performing signal superposition processing on the I phase compensated signals to obtain a coherent accumulation signal.
[0005] In some embodiments, the adaptive filtering function corresponding to the i-th group of signals to be filtered is calculated using the i-th target velocity parameter and the i-th target acceleration parameter, wherein the i-th target velocity parameter and the i-th target acceleration parameter are obtained by performing calculations on the i-th group of signals to be filtered using a traversal search algorithm or an estimation algorithm.
[0006] In some embodiments, the method of using an adaptive filtering function corresponding to the i-th group of signals to be filtered to perform frequency filtering on the i-th group of signals to be filtered to extract the i-th filtered signal includes: performing frequency domain transformation on the i-th group of signals to be filtered to obtain the i-th group of frequency domain signals; using the adaptive filtering function corresponding to the i-th group of signals to be filtered to process the i-th group of frequency domain signals to obtain the i-th filtered frequency domain signal; and performing time domain transformation on the i-th filtered frequency domain signal to obtain the i-th filtered signal.
[0007] In some embodiments, the i-th filtered signal is subjected to phase compensation processing in the azimuth dimension to obtain the i-th phase compensated signal, including: performing a positional multiplication operation on the i-th filtered signal and the i-th matched filter function to realize phase compensation processing to obtain the i-th matched filtered signal; performing Fourier transform on the i-th matched filtered signal to obtain the i-th phase compensated signal.
[0008] In some embodiments, the i-th matched filter function is obtained by: using an acceleration estimation algorithm to perform calculations on the i-th filter signal to obtain an i-th acceleration value; using the i-th acceleration value to establish the i-th matched filter function.
[0009] In some embodiments, the range resolution is obtained by calculating the bandwidth of a transmit pulse of a radar transmitter.
[0010] In some embodiments, the method further comprises: storing the coherent accumulation signal in a data memory.
[0011] In some embodiments, the expression of the i-th adaptive filter function satisfies:
[0012]
[0013] Among them, H i is the i-th adaptive filter function, rect(·) is the rectangular pulse function, v i is the i-th target speed parameter, a i is the acceleration parameter of the i-th target, f is the frequency of the i-th group of signals to be filtered, λ is the central wavelength of the radar transmission signal, t m is the time series of the radar transmitter's transmit pulses.
[0014] In some embodiments, the expression of the i-th filtered signal satisfies:
[0015]
[0016] Among them, sinc(u)=sin(u) / u, IFFT(·) is the inverse Fourier transform, FFT(·) refers to the Fourier transform, is the i-th group of signals to be filtered, B is the bandwidth of the transmit pulse of the radar transmitter, is the sampling time series of the radar receiver, R 0 is the target initial position coordinate, c is the speed of light, j is the imaginary unit, λ is the central wavelength of the radar transmission signal, and exp(·) represents the exponential function with the natural constant e as the base.
[0017] In some embodiments, the expression of the i-th phase compensation signal satisfies:
[0018]
[0019] in, is the i-th phase compensation signal, H i ′ is the i-th matched filter function, mT p is the total duration of the radar transmitter pulse, a i ′ is the i-th acceleration value.
[0020] Compared with the prior art, the present invention has the following beneficial effects:
[0021] In view of the problem that traditional phase error compensation methods have poor performance when dealing with dense targets, the present invention provides a dense target coherent accumulation method based on an adaptive filter. The method performs pulse compression processing on the obtained echo signal and then averages the compressed signal to obtain multiple groups of signals to be filtered. Each group of signals to be filtered after averaged is filtered by using different adaptive filtering functions to extract multiple target signals (or filtered signals) with different frequencies to avoid missing weak target signals. After obtaining multiple target signals, phase compensation processing is performed on each target signal to achieve coherent accumulation of dense target signals, reduce the defocusing probability in the Doppler dimension when performing data analysis on the received radar signal, and effectively improve the accuracy of data analysis. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] Figure 1 It is a flowchart of a method for dense target coherent accumulation based on an adaptive filter provided by an embodiment of the present invention;
[0023] Figure 2 It is a simulation example diagram before and after using the dense target coherent accumulation method based on the adaptive filter provided in an embodiment of the present invention. DETAILED DESCRIPTION
[0024] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.
[0025] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine different embodiments or examples described in this specification.
[0026] Although the present invention is described herein in conjunction with various embodiments, in the process of implementing the claimed invention, those skilled in the art may understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude multiple situations. A single processor or other unit may implement several functions listed in the claims. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.
[0027] Now, in conjunction with the accompanying drawings, a dense target coherent accumulation method based on an adaptive filter provided by the present invention is described in detail.
[0028] Figure 1 FIG. 1 is a flow chart of a method for dense target coherent accumulation based on an adaptive filter provided by an embodiment of the present invention. Figure 1 As shown, the method includes:
[0029] Step 110: Perform pulse compression processing on the acquired echo signals containing multiple targets in the distance dimension to obtain a group of compressed signals.
[0030] Here, after the traditional radar transmits the linear frequency modulation signal, the radar receiver periodically receives the linear frequency modulation signal reflected by the target, and processes the echo signal received in each cycle in turn. Here, in the current cycle, the signal after pulse compression of the received echo signal containing K targets can be expressed as:
[0031]
[0032] Wherein, sinc(u)=sin(u) / u; B is the bandwidth of the transmitted signal; is the radar receiver sampling time series; t m The time sequence of pulses emitted by the radar transmitter; It is the delay time for the radar transmitted signal to be received by the receiver after being reflected by the target; is the relative distance between the target and the radar, R 0 is the target initial position coordinate, v i is the moving speed of the i-th target, a i is the acceleration of the ith target, c is the speed of light; exp(·) represents the exponential function with the natural constant e as the base; j represents the imaginary unit; λ is the central wavelength of the radar emission signal; and π is the circumference of a circle.
[0033] It should be noted that the echo signal can be pulse compressed using radar receiver hardware or conventional signal processing methods.
[0034] Step 120: using the distance resolution, evenly divide the signal sequence of the compressed signal in the distance dimension to obtain I groups of signals to be filtered, where I is a positive integer greater than or equal to 1.
[0035] Here, each cell in the original one-dimensional range image data of the radar corresponds to the actual distance from the radar in physical space. The distance interval corresponding to adjacent range cells is consistent with the radar range resolution. In other words, the range resolution can be obtained by calculating the bandwidth B of the radar transmitter's transmission pulse, which can determine the size of the averaging interval. For example, the length of the range resolution is R 0 , when using this distance resolution for division, if the length of the last group of signals to be filtered is less than R 0 , the last group of signals to be filtered can be padded with zeros.
[0036] In a possible implementation, assuming that there are K targets in the range unit, the i-th group of signals to be filtered is The expression can be expressed as:
[0037]
[0038] Step 130: Use the adaptive filtering function corresponding to the i-th group of signals to be filtered to perform frequency filtering on the i-th group of signals to be filtered, and extract the i-th filtered signal, where i is less than or equal to I.
[0039] Here, after obtaining I groups of signals to be filtered, signal extraction is performed on each group of signals to be filtered in turn, or in other words, the various types of signals mixed together are separated. Specifically, step 130 includes: performing frequency domain transformation on the i-th group of signals to be filtered to obtain the i-th group of frequency domain signals; using the adaptive filter function corresponding to the i-th group of signals to be filtered to process the i-th group of frequency domain signals to obtain the i-th filtered frequency domain signal; performing time domain transformation on the i-th filtered frequency domain signal to obtain the i-th filtered signal. Among them, the adaptive filter function corresponding to the i-th group of signals to be filtered is calculated using the i-th target speed parameter and the i-th target acceleration parameter, and the i-th target speed parameter and the i-th target acceleration parameter are obtained by calculating and processing the i-th group of signals to be filtered using a traversal search algorithm or an estimation algorithm.
[0040] In one possible implementation, the expression of the i-th adaptive filter function satisfies:
[0041]
[0042] Among them, H i is the i-th adaptive filter function, rect(·) is the rectangular pulse function, v i is the i-th target speed parameter, a i is the acceleration parameter of the i-th target, f is the frequency of the i-th group of signals to be filtered, λ is the central wavelength of the radar transmission signal, t m is the time series of the radar transmitter's transmit pulses.
[0043] Exemplarily, first, in order to improve the calculation speed, the i-th group of signals to be filtered is Fourier transformed to transform it from the time domain to the frequency domain to obtain the i-th group of frequency domain signals; then, the i-th group of frequency domain signals is substituted into the i-th adaptive filter function for calculating frequency filtering, and then the obtained filtered signal is inversely Fourier transformed and converted to the time domain again, and the above operation is repeated for each group of signals to be filtered until the i-th filtered signal is obtained. Here, the i-th group of signals to be filtered and the i-th filtered frequency domain signal can be Fourier transformed and inverse Fourier transformed by the FFT hardware module. Specifically, when the adaptive filter corresponding to the i-th group of signals to be filtered is designed as a digital filter, a multiplication calculator can be used to perform data point multiplication; when the adaptive filter filter corresponding to the i-th group of signals to be filtered is a mid-pass hardware filter, the signal filtering can be completed by passing the signal through the filter hardware.
[0044] It should be noted that the traversal search algorithm or estimation algorithm involved in the present invention is an existing algorithm, wherein the estimation algorithm may include: WVD algorithm, GRFT algorithm, FrFT algorithm, TST algorithm and LVD algorithm, etc.
[0045] It should be noted that the adaptive filter function (or adaptive filter) corresponding to the i-th group of signals to be filtered may also be designed using hardware adaptive design, for example, designed as a medium-pass filter.
[0046] In one possible implementation, the i-th filtered signal The expression satisfies:
[0047]
[0048] Among them, sinc(u)=sin(u) / u, IFFT(·) is the inverse Fourier transform, FFT(·) refers to the Fourier transform, is the i-th group of signals to be filtered, B is the bandwidth of the radar transmitter’s transmission pulse, is the sampling time series of the radar receiver, R 0 is the target initial position coordinate, c is the speed of light, j is the imaginary unit, λ is the central wavelength of the radar transmission signal, and exp(·) represents the exponential function with the natural constant e as the base.
[0049] By using different types of adaptive filters for filtering, target signals of different frequencies can be extracted, signal separation under dense targets can be completed, and weak targets can be avoided from being missed.
[0050] Step 140: Perform phase compensation processing on the i-th filtered signal in the azimuth dimension to obtain the i-th phase compensated signal, and continue to process the i+1-th group of filtered signals to obtain the i+1-th phase compensated signal, until the I-th phase compensated signal is obtained.
[0051] Here, an example of the execution process of obtaining the i-th phase compensation signal is given. Specifically, a bitwise multiplication operation is performed on the i-th filter signal and the i-th matched filter function to implement phase compensation processing to obtain the i-th matched filter signal; and a Fourier transform is performed on the i-th matched filter signal to obtain the i-th phase compensation signal.
[0052] Here, the i-th matched filter function is obtained by: using an acceleration estimation algorithm, performing operation processing on the i-th filter signal to obtain the i-th acceleration value; using the i-th acceleration value, establishing the i-th matched filter function. Exemplarily, the i-th matched filter function can be expressed as: Among them, a i ′ is the i-th acceleration value, t m is the time series of the radar transmitter's transmit pulses.
[0053] In one possible implementation, the expression of the i-th phase compensation signal satisfies:
[0054]
[0055] in, is the i-th phase compensation signal, H i ′ is the i-th matched filter function, mT p is the total duration of the radar transmitter pulse, a i ′ is the i-th acceleration value.
[0056] After obtaining the i-th phase compensation signal, continue to use the i+1-th filtered signal to establish the i+1-th matched filter function, perform a bitwise multiplication operation on the i+1-th filtered signal and the i+1-th matched filter function to obtain the i+1-th matched filtered signal; perform Fourier transform on the i+1-th matched filtered signal to obtain the i+1-th phase compensation signal, and repeat the above operation for each filtered signal until the I-th phase compensation signal is obtained.
[0057] By performing phase compensation on the extracted multiple filtered signals, coherent accumulation of different target signals can be achieved, reducing the defocus probability in the Doppler dimension when performing data analysis on the received radar signals, and effectively improving the accuracy of data analysis.
[0058] Step 150: Perform signal superposition processing on the I phase compensation signals to obtain a coherent accumulation signal.
[0059] In one possible implementation, the coherent integration signal can be expressed as: After obtaining the coherent accumulation signal of the current cycle, the method further includes: using a data storage device to store the coherent accumulation signal. It should be understood that the present invention does not limit the storage method of the coherent accumulation signal, and the coherent accumulation signal can also be stored by establishing a database or storing it on a hard disk.
[0060] After the echo signal processing of the current cycle is completed, steps 110 - 150 are repeated to process the echo signal received in the next cycle.
[0061] In view of the problem that traditional phase error compensation methods have poor performance when dealing with dense targets, the present invention provides a dense target coherent accumulation method based on an adaptive filter. The method performs pulse compression processing on the obtained echo signal and then averages the compressed signal to obtain multiple groups of signals to be filtered. Each group of signals to be filtered after averaged is filtered by using different adaptive filtering functions to extract multiple target signals (or filtered signals) with different frequencies to avoid missing weak target signals. After obtaining multiple target signals, phase compensation processing is performed on each target signal to achieve coherent accumulation of dense target signals, reduce the defocusing probability in the Doppler dimension when performing data analysis on the received radar signal, and effectively improve the accuracy of data analysis.
[0062] In order to verify the performance of the dense target coherent accumulation method based on adaptive filter provided by the present invention, MATLAB simulation software is used for verification. Specifically, the experimental parameters used in the simulation are shown in Table 1 below.
[0063] Table 1
[0064] Center frequency (GHz) 5 Target 2 horizontal coordinate (m) -90 Bandwidth (MHz) 10 Target 2 vertical coordinate (m) 500 Pulse repetition frequency (Hz) 500 Target 2 speed (m / s) -14 Target 1 horizontal coordinate (m) 100 Signal-to-noise ratio (dB) 12 Target 1 vertical coordinate (m) 500 C / N Ratio(dB) 30 Target 1 speed (m / s) 10
[0065] The simulation results are as follows Figure 2 As shown in (1) and (2) in , assuming that there are two targets with different velocities and accelerations in the same distance ring from the radar, Figure 2 (1) is the range Doppler spectrum before phase compensation, Figure 2 (2) is the range Doppler spectrum processed by the dense target coherent accumulation method based on adaptive filter provided by the present invention. By comparing the two figures, it can be found that under strong ground clutter interference, the method can still estimate the target phase error and complete the compensation.
[0066] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.
Claims
1. A dense target coherent accumulation method based on adaptive filter, characterized in that: include: Performing pulse compression processing on the acquired echo signals containing multiple targets in the distance dimension to obtain a group of compressed signals; Using the distance resolution, the signal sequence of the compressed signal is evenly divided in the distance dimension to obtain I groups of signals to be filtered, where I is a positive integer greater than or equal to 1; Using the adaptive filtering function corresponding to the i-th group of signals to be filtered, frequency filtering is performed on the i-th group of signals to be filtered, and an i-th filtered signal is extracted, where i is less than or equal to I; Performing phase compensation processing on the i-th filtered signal in the azimuth dimension to obtain an i-th phase compensated signal, and continuing to process the i+1-th group of signals to be filtered to obtain an i+1-th phase compensated signal, until an I-th phase compensated signal is obtained; Signal superposition processing is performed on I phase compensation signals to obtain a coherent accumulation signal.
2. The method for dense target coherent accumulation based on adaptive filter according to claim 1, characterized in that: The adaptive filtering function corresponding to the i-th group of signals to be filtered is calculated using the i-th target velocity parameter and the i-th target acceleration parameter, wherein the i-th target velocity parameter and the i-th target acceleration parameter are obtained by performing calculations on the i-th group of signals to be filtered using a traversal search algorithm or an estimation algorithm.
3. The method for dense target coherent accumulation based on adaptive filter according to claim 2, characterized in that: The method of using the adaptive filtering function corresponding to the i-th group of signals to be filtered to perform frequency filtering on the i-th group of signals to be filtered to extract the i-th filtered signal comprises: Performing frequency domain transformation on the i-th group of signals to be filtered to obtain an i-th group of frequency domain signals; Using the adaptive filtering function corresponding to the i-th group of signals to be filtered, the i-th group of frequency domain signals is processed to obtain the i-th filtered frequency domain signal; Performing a time domain transform on the i-th filtered frequency domain signal to obtain the i-th filtered signal.
4. The method for dense target coherent accumulation based on adaptive filter according to claim 1, characterized in that: Performing phase compensation processing on the i-th filtered signal in the azimuth dimension to obtain an i-th phase compensated signal includes: Performing a bitwise multiplication operation on the i-th filtered signal and the i-th matched filter function to achieve phase compensation processing to obtain an i-th matched filter signal; Performing Fourier transform on the i-th matched filter signal to obtain the i-th phase compensation signal.
5. The method for dense target coherent accumulation based on adaptive filter according to claim 4, characterized in that: The i-th matched filter function is obtained by: Using an acceleration estimation algorithm, the i-th filtered signal is processed to obtain an i-th acceleration value; The i-th matched filter function is established using the i-th acceleration value.
6. The method for dense target coherent accumulation based on adaptive filter according to claim 1, characterized in that: The distance resolution is obtained by calculating the bandwidth of the transmission pulse of the radar transmitter.
7. The method for dense target coherent accumulation based on adaptive filter according to claim 1, characterized in that: The method further includes: storing the coherent accumulation signal in a data memory.
8. The method for dense target coherent accumulation based on adaptive filter according to claim 2, characterized in that: The expression of the i-th adaptive filter function satisfies: Among them, H i is the i-th adaptive filter function, rect(·) is the rectangular pulse function, v i is the i-th target speed parameter, a i is the acceleration parameter of the i-th target, f is the frequency of the i-th group of signals to be filtered, λ is the central wavelength of the radar transmission signal, t m is the time series of the radar transmitter's transmit pulses.
9. The method for dense target coherent accumulation based on adaptive filter according to claim 3, characterized in that: The expression of the i-th filtered signal satisfies: Among them, sinc(u)=sin(u) / u, IFFT(·) is the inverse Fourier transform, FFT(·) refers to the Fourier transform, is the i-th group of signals to be filtered, B is the bandwidth of the transmit pulse of the radar transmitter, is the sampling time series of the radar receiver, R0 is the initial position coordinate of the target, c is the speed of light, j is the imaginary unit, λ is the central wavelength of the radar transmission signal, and exp(·) represents the exponential function with the natural constant e as the base.
10. The method for dense target coherent accumulation based on adaptive filter according to claim 5, characterized in that: The expression of the i-th phase compensation signal satisfies: in, is the i-th phase compensation signal, H i ′ is the i-th matched filter function, mT p is the total duration of the radar transmitter pulse, a i ′ is the i-th acceleration value.