A method and system for adaptive suppression of motion clutter based on filter bank

Abstract

The embodiment of the present application discloses a filter bank based adaptive suppression method and system for moving clutter. The method comprises designing a moving target indication filter with a notch at zero frequency, and obtaining a weight coefficient vector of the moving target indication filter; shifting the moving target indication filter on the frequency axis to obtain a filter bank and a weight coefficient matrix of the filter bank; solving the weight coefficient vector of the optimal filter according to the weight coefficient matrix; using the optimal filter to perform cancellation processing on an input signal containing a clutter signal and a noise signal; performing first non-coherent accumulation processing on the signal after cancellation processing, and performing second non-coherent accumulation processing on the input signal; and using a clutter profile or target detection to distinguish whether the results of the first non-coherent accumulation processing and the second non-coherent accumulation processing are output. The embodiment effectively suppresses the clutter and extracts the target signal, and can further improve the detection performance of the radar in a complex and variable environment.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing. More specifically, it relates to an adaptive method and system for suppressing moving clutter based on filter banks. Background Technology

[0002] Radars typically face complex clutter environments during operation, with certain frequency bands and radar systems experiencing particularly complex clutter environments. This is primarily due to factors such as wide radar beamwidth, high beam sidelobes, and sensitivity to weather clutter. Because of these complex clutter environments, targets are often submerged, severely impacting the radar's detection capabilities. To effectively extract signals from strong clutter backgrounds and improve radar detection performance in complex and variable environments, clutter suppression and corresponding target detection processing methods are necessary.

[0003] Existing moving target indication (MTI) methods can effectively suppress stationary clutter and extract target echo signals to improve the signal-to-clutter ratio of radar echo signals, thereby enhancing detection capabilities. However, in the presence of moving clutter such as meteorological clutter, these methods cannot effectively filter out clutter signals. Existing adaptive MTI methods can effectively filter out moving clutter and extract target echo signals, improving radar detection performance. However, when radar target signals are significantly affected by geographical location and weather conditions, these methods cannot effectively suppress clutter signals. Existing pulse Doppler methods can effectively filter out clutter near zero frequency and suppress meteorological clutter even when it is outside the filter passband. However, the filter response is easily affected by clutter interference, weakening the clutter suppression capability. Summary of the Invention

[0004] The purpose of this invention is to provide an adaptive method and system for suppressing motion clutter based on filter banks, so as to solve at least one of the problems existing in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] The first aspect of this invention provides an adaptive motion clutter suppression method based on a filter bank, the method comprising:

[0007] Design a moving target display filter with a notch at zero frequency, and obtain the weight coefficient vector of the moving target display filter;

[0008] The moving target display filter is translated on the frequency axis to obtain the filter bank and the weight coefficient matrix of the filter bank;

[0009] The optimal filter's weight coefficient vector is obtained from the weight coefficient matrix.

[0010] The optimal filter is used to cancel out the input signal containing clutter and noise signals;

[0011] The signal after cancellation processing is subjected to a first noncoherent accumulation process, and the input signal is subjected to a second noncoherent accumulation process;

[0012] The clutter profile map or target detection is used to determine whether the results of the first noncoherent accumulation processing and the second noncoherent accumulation processing are output.

[0013] Optionally, the step of solving for the optimal filter's weight coefficient vector based on the weight coefficient matrix includes...

[0014] The weighting coefficient vector that minimizes the output power of the clutter signal is calculated by solving a linearly constrained optimization problem based on the response of the target signal.

[0015] Optionally, the formula for calculating the weight coefficient vector that minimizes the output power of the clutter signal is as follows:

[0016]

[0017] In the formula, S0 is a constant vector; R c Let be the covariance matrix of the clutter signal vector sequence.

[0018] Optionally, the constant vector is

[0019]

[0020] In the formula, f d T is the Doppler frequency; r The pulse repetition period; (·) T For transpose; N is the number of pulses.

[0021] Optionally, the covariance matrix of the clutter signal vector sequence satisfies the following formula:

[0022]

[0023] In the formula, P c W is the output power of the clutter signal; m Let be the weight coefficient matrix of the filter bank; (·) H This is the conjugate transpose.

[0024] Optionally, the function for solving the linearly constrained optimization problem based on the response of the target signal is:

[0025]

[0026] In the formula, S0 is a constant vector; R c W is the covariance matrix of the clutter signal vector sequence; m Let be the weight coefficient matrix of the filter bank; (·)H This is the conjugate transpose.

[0027] Optionally, the weight coefficient matrix of the filter bank is

[0028]

[0029] In the formula, w 01 ,w 02 ,...,w 0N The weighting coefficient vector for each pulse; f m The Doppler frequency for each filter; T r The pulse repetition period is m = 1, 2, ..., M; M is the number of filters.

[0030] Optionally, the calculation formula for the first noncoherent accumulation processing of the canceled signal is as follows:

[0031]

[0032] In the formula, y i (n) is the output signal after the input signal has undergone the cancellation process; i = 1, 2...N, I is the total number of pulses.

[0033] Optionally, the calculation formula for the second noncoherent accumulation processing of the input signal is as follows:

[0034]

[0035] In the formula, x i (n) represents the input signal; i = 1, 2... N, and I is the total number of pulses.

[0036] A second aspect of the present invention provides a motion clutter adaptive suppression system based on a filter bank, the system comprising:

[0037] The filter design module is used to design a moving target display filter with a notch at zero frequency and to obtain the weight coefficient vector of the moving target display filter.

[0038] The filter bank design module is used to translate the moving target display filter on the frequency axis to obtain the filter bank and the weight coefficient matrix of the filter bank;

[0039] The calculation module is used to solve for the weight coefficient vector of the optimal filter based on the weight coefficient matrix;

[0040] The cancellation processing module is used to cancel the input signal containing clutter and noise signals using the optimal filter;

[0041] The noncoherent accumulation processing module is used to perform a first noncoherent accumulation processing on the signal after cancellation processing, and a second noncoherent accumulation processing on the input signal;

[0042] The discrimination module is used to determine whether to output the results of the first noncoherent accumulation processing and the second noncoherent accumulation processing using clutter contour maps or target detection.

[0043] The beneficial effects of this invention are as follows:

[0044] The present invention provides an adaptive motion clutter suppression method based on filter banks, which can effectively suppress clutter and extract target signals under conditions where the terrain and adverse weather conditions are significant, thereby further improving the detection performance of radar in complex and variable environments. Attached Figure Description

[0045] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0046] Figure 1 The flowchart illustrates the motion clutter adaptive suppression method based on filter banks provided in an embodiment of the present invention.

[0047] Figure 2 The diagram shows the frequency response of a single notch filter used in the motion clutter adaptive suppression method based on filter banks provided in this embodiment of the invention.

[0048] Figure 3 The diagram shows the frequency response of a dual-notch filter used in the motion clutter adaptive suppression method based on filter banks provided in this embodiment of the invention.

[0049] Figure 4 The diagram shows the clutter suppression results without using the filter bank-based adaptive motion clutter suppression method provided in this embodiment of the invention.

[0050] Figure 5 The diagram shows the clutter suppression results achieved using the filter bank-based adaptive motion clutter suppression method provided in this embodiment of the invention. Detailed Implementation

[0051] To more clearly illustrate the present invention, the following description, in conjunction with embodiments and accompanying drawings, further explains the invention. Similar components in the drawings are indicated by the same reference numerals. Those skilled in the art should understand that the specific description below is illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.

[0052] Typical solutions to the problem of clutter suppression in complex and variable environments include Moving Target Indication (MTI), Adaptive Moving Target Indication (AMTI), and Pulse Doppler (PD).

[0053] Moving target indication (MTI) is used in scenarios where clutter power is concentrated near the zero frequency band. In this case, clutter is similar to stationary targets, with its amplitude changing little over time within adjacent periods, while the echo signal amplitude of a moving target exhibits a fluctuating "butterfly effect" over time. MTI technology extracts the moving target echo from a signal containing various stationary clutter, stationary (or slow-moving) target echoes, and moving target echoes based on the spectral differences between moving target and clutter signals. This improves the signal-to-clutter ratio of the radar echo signal and further allows for the acquisition of moving target parameters.

[0054] The Adaptive Moving Target Display (AMTI) method is used in scenarios where moving clutter exists. In such cases, the center of the clutter spectrum is constantly changing. The AMTI method can move the notch of the filter in real time so that the notch of the filter can always be aligned with the center of the clutter spectrum, thereby effectively suppressing clutter.

[0055] The pulse Doppler method primarily uses a Doppler filter bank to cover the entire repetition frequency range to suppress clutter. However, this method uses a relatively high pulse repetition frequency, which can easily cause distance ambiguity, thus requiring a large number of Doppler filter banks.

[0056] Existing moving target indication (MTI) methods can effectively suppress stationary clutter and extract target echo signals to improve the signal-to-clutter ratio of radar echo signals, thereby enhancing detection capabilities. However, in the presence of moving clutter such as meteorological clutter, these methods cannot effectively filter out clutter signals. Existing adaptive MTI methods can effectively filter out moving clutter and extract target echo signals, improving radar detection performance. However, when radar target signals are significantly affected by geographical location and weather conditions, these methods cannot effectively suppress clutter signals. Existing pulse Doppler methods can effectively filter out clutter near zero frequency and suppress meteorological clutter even when it is outside the filter passband. However, the filter response is easily affected by clutter interference, weakening the clutter suppression capability.

[0057] In view of this, one embodiment of the present invention provides a motion clutter adaptive suppression method based on a filter bank. The method includes designing a moving target display filter with a notch at zero frequency and obtaining the weight coefficient vector of the moving target display filter; translating the moving target display filter on the frequency axis to obtain a filter bank and a weight coefficient matrix of the filter bank; solving for the weight coefficient vector of the optimal filter based on the weight coefficient matrix; using the optimal filter to perform cancellation processing on an input signal containing clutter and noise signals; performing a first noncoherent accumulation processing on the canceled signal and a second noncoherent accumulation processing on the input signal; and using a clutter profile map or target detection to determine whether the results of the first and second noncoherent accumulation processing are output.

[0058] Specifically, this embodiment provides a motion clutter adaptive suppression method based on filter banks to solve the problem of target being submerged in complex clutter environments.

[0059] Furthermore, such as Figure 1 As shown, this embodiment processes the input signal through two channels. Channel one uses an MTI filter with a notch at zero frequency. This filter is translated along the frequency axis to obtain a set of filter weight coefficient matrices. The weight coefficient matrix that minimizes clutter output power is selected as the optimal filter, and the input signal is then canceled. The canceled signal is then subjected to non-coherent accumulation processing. Channel two directly performs non-coherent accumulation processing on the input signal. The output points of both channels are used to determine whether they are the final output points through clutter contour mapping or target detection.

[0060] This embodiment can effectively suppress clutter and extract target signals even under conditions where geographical location and severe weather have a significant impact, thereby further improving the radar's detection performance in complex and ever-changing environments.

[0061] In a specific example, the motion clutter adaptive suppression method based on filter banks includes the following steps.

[0062] Step 1: Design an MTI filter with a notch at zero frequency. The weight coefficient vector of the filter is W0 = [w 01 ,w 02 ,...,w 0N ] T ;

[0063] Step 2: Translate the zero-frequency filter on the frequency axis to obtain the weight coefficient vector of the filter bank.

[0064] Step 3: Find the weighting coefficient vector W that minimizes the clutter output power. opt ;

[0065] Step 4: Perform cancellation processing on the input signal;

[0066] Step 5: Perform non-coherent accumulation processing on the canceled signal;

[0067] Step 6: Perform non-coherent accumulation processing directly on the input signal;

[0068] Step 7: Select the output result based on the clutter profile map or target detection.

[0069] This embodiment mainly addresses the problem of reduced radar target detection capability in complex clutter environments. Specifically, it proposes a motion clutter adaptive suppression method based on filter banks, which can be used for clutter suppression processing of radar in complex and variable environments.

[0070] In one possible implementation, solving for the optimal filter weight coefficient vector based on the weight coefficient matrix includes calculating the weight coefficient vector that minimizes the output power of the clutter signal by solving a linearly constrained optimization problem based on the response of the target signal.

[0071] In one possible implementation, the formula for calculating the weight coefficient vector that minimizes the output power of the clutter signal is as follows:

[0072]

[0073] In the formula, S0 is a constant vector; R c Let be the covariance matrix of the clutter signal vector sequence.

[0074] In one possible implementation, the constant vector is

[0075]

[0076] In the formula, f d T is the Doppler frequency; r The pulse repetition period; (·) T For transpose; N is the number of pulses.

[0077] In one possible implementation, the covariance matrix of the clutter signal vector sequence satisfies the following formula:

[0078]

[0079] In the formula, P c W is the output power of the clutter signal; m Let be the weight coefficient matrix of the filter bank; (·) H This is the conjugate transpose.

[0080] In one possible implementation, the function for solving the linearly constrained optimization problem based on the response of the target signal is:

[0081]

[0082] In the formula, S0 is a constant vector; R c W is the covariance matrix of the clutter signal vector sequence; m Let be the weight coefficient matrix of the filter bank; (·) H This is the conjugate transpose.

[0083] In one possible implementation, the weight coefficient matrix of the filter bank is:

[0084]

[0085] In the formula, w 01 ,w 02 ,...,w 0N The weighting coefficient vector for each pulse; f m The Doppler frequency for each filter; T r The pulse repetition period is m = 1, 2, ..., M; M is the number of filters.

[0086] In this embodiment, the adaptive clutter suppression method focuses on the fact that the notch of the filter can be moved in real time, so that the notch of the filter can always be aligned with the center position of the clutter spectrum, thereby effectively suppressing clutter.

[0087] In a specific example, the weighting coefficient vector W that minimizes clutter output power in step 3 opt The calculation method is as follows:

[0088] Step 31: Assuming the radar echo signal contains a target signal, the echo signal is as follows:

[0089] x(n) = s(n) + c(n) + n(n)

[0090] In the formula, s(n) is the echo signal vector; c(n) is the clutter vector sequence; n(n) is the noise vector sequence, n=1,2,...,N.

[0091] Step 32: The weight coefficient vector of the filter bank is W m The output signal is then expressed as

[0092]

[0093] In the formula, (·) H This is the conjugate transpose.

[0094] Step 33: The output power of the clutter signal is expressed as...

[0095]

[0096] In the formula, (·)* To obtain conjugate; R c Let be the covariance matrix of the clutter.

[0097] Step 34: Optimal weight coefficient W opt The formula can be obtained through the following linearly constrained optimization problem, which is as follows:

[0098]

[0099] In the formula, the constraint condition represents the response to the target signal s(n), and f represents a constant vector; d T is the Doppler frequency; r The pulse repetition period; (·) T This is a transpose.

[0100] The optimal weight coefficient vector is then expressed as:

[0101] In one possible implementation, the noncoherent accumulation processing in step 5 involves accumulating the amplitude of the canceled signal. The calculation formula for the first noncoherent accumulation processing of the canceled signal is as follows:

[0102]

[0103] In the formula, y i (n) is the output signal after the input signal has undergone the cancellation process; i = 1, 2...N, I is the total number of pulses.

[0104] In one possible implementation, the noncoherent accumulation processing in step 6 involves accumulating the amplitude of the input target signal, and the calculation formula for the second noncoherent accumulation processing of the input signal is as follows:

[0105]

[0106] In the formula, x i (n) represents the input signal; i = 1, 2... N, and I is the total number of pulses.

[0107] In a specific example, a uniform linear array with 8 array elements, 16 effective pulses, a scattering point echo amplitude of 0.005, a target amplitude of 1, a target initial phase and elevation angle of 30°, a target azimuth angle of 0, a Doppler frequency of 100Hz, a pulse repetition frequency of 300Hz, and channel one employs both single-notch and double-notch filters.

[0108] Specifically, the single-notch Doppler frequency is 0Hz, and the frequency response is as follows: Figure 2 As shown, the notch Doppler frequencies of the dual-notch filter are 0Hz and 300Hz, and the frequency response is as follows. Figure 3 As shown.

[0109] from Figure 2 and Figure 3 As can be seen, the filter frequency response produces a deep notch at the Doppler velocity position, which is beneficial for eliminating clutter.

[0110] Furthermore, assume the target is located at point 147 in the distance unit, the target's radial velocity is 50 m / s, and the target's Doppler frequency is 200 Hz.

[0111] The result of processing without clutter suppression is as follows Figure 4 As shown, the output result after clutter suppression Figure 5 As shown, from Figure 4 and Figure 5 As can be seen, the radar can extract the corresponding target signal after clutter suppression.

[0112] The motion clutter adaptive suppression method based on filter banks provided in this embodiment effectively solves the clutter suppression problem in complex terrain and environmental scenarios. The input signal is processed through two channels. Channel one uses an MTI filter with a notch at zero frequency. This filter is translated along the frequency axis to obtain a set of filter weight coefficient matrices. The weight coefficient matrix that minimizes the clutter output power is selected as the optimal filter, and cancellation processing is performed. The cancelled signal is then subjected to non-coherent accumulation processing. Channel two performs non-coherent accumulation processing on the input signal. The output points of both channels are used to determine whether they are the final output points through clutter contour mapping or target detection.

[0113] This embodiment can effectively suppress clutter and extract target signals even under conditions where geographical location and severe weather conditions are significant, thereby further improving the radar's detection performance in complex and variable environments.

[0114] Another embodiment of the present invention provides a motion clutter adaptive suppression system based on a filter bank. The system includes a filter design module for designing a moving target display filter with a notch at zero frequency and obtaining the weight coefficient vector of the moving target display filter; a filter bank design module for translating the moving target display filter on the frequency axis to obtain a filter bank and a weight coefficient matrix of the filter bank; a calculation module for solving for the weight coefficient vector of the optimal filter based on the weight coefficient matrix; a cancellation processing module for using the optimal filter to perform cancellation processing on an input signal containing clutter and noise signals; a noncoherent accumulation processing module for performing a first noncoherent accumulation processing on the canceled signal and a second noncoherent accumulation processing on the input signal; and a discrimination module for using a clutter profile map or target detection to determine whether the results of the first and second noncoherent accumulation processing are output.

[0115] This embodiment proposes a motion clutter adaptive suppression system based on filter banks to address the problem of poor clutter suppression capability in complex geographical and weather scenarios.

[0116] In this embodiment, the input signal is sent to two channels for processing. Channel 1 uses a filter bank method to select the optimal filter for clutter suppression. Channel 2 directly performs non-coherent accumulation processing on the input signal. The output results of the two channels are selected by clutter profile map or target detection discrimination to output the final result, thereby realizing the clutter suppression function.

[0117] This embodiment can effectively suppress clutter and extract target signals even under conditions where geographical location and severe weather conditions are significant, thereby further improving the radar's detection performance in complex and variable environments.

[0118] In the description of this invention, it should be noted that the terms "upper," "lower," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Unless otherwise expressly specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication between two elements. For those skilled in the art, the specific meaning of the above terms in this invention can be understood according to the specific circumstances.

[0119] It should also be noted that, in the description of this invention, relational terms such as "first" and "second" are used merely 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 a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0120] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. For those skilled in the art, other variations or modifications can be made based on the above description. It is impossible to exhaustively list all the implementation methods here. All obvious variations or modifications derived from the technical solutions of the present invention are still within the protection scope of the present invention.

Claims

1. A method for adaptive suppression of motion clutter based on filter banks, characterized in that, The method includes Design a moving target display filter with a notch at zero frequency, and obtain the weight coefficient vector of the moving target display filter; The moving target display filter is translated on the frequency axis to obtain the filter bank and the weight coefficient matrix of the filter bank; The optimal filter's weight coefficient vector is obtained from the weight coefficient matrix. The optimal filter is used to cancel out the input signal containing clutter and noise signals; The signal after cancellation processing is subjected to a first noncoherent accumulation process, and the input signal is subjected to a second noncoherent accumulation process; The clutter profile map or target detection is used to determine whether the results of the first noncoherent accumulation processing and the second noncoherent accumulation processing should be output, and the output result is selected based on the clutter profile map or target detection.

2. The adaptive motion clutter suppression method based on filter banks according to claim 1, characterized in that, The step of solving for the optimal filter weight coefficient vector based on the weight coefficient matrix includes... The weighting coefficient vector that minimizes the output power of the clutter signal is calculated by solving a linearly constrained optimization problem based on the response of the target signal.

3. The adaptive motion clutter suppression method based on filter banks according to claim 2, characterized in that, The formula for calculating the weighting vector that minimizes the output power of the clutter signal is as follows: In the formula, It is a constant vector; Let be the covariance matrix of the clutter signal vector sequence.

4. The adaptive motion clutter suppression method based on filter banks according to claim 3, characterized in that, The constant vector is In the formula, The frequency is the Doppler frequency. The pulse repetition period; For transpose; This represents the number of pulses.

5. The adaptive motion clutter suppression method based on filter banks according to claim 4, characterized in that, The covariance matrix of the clutter signal vector sequence satisfies the following formula: In the formula, The output power of the clutter signal; The weight coefficient matrix of the filter bank; This is the conjugate transpose.

6. The adaptive motion clutter suppression method based on filter banks according to claim 4, characterized in that, The function for solving the linearly constrained optimization problem based on the response of the target signal is: In the formula, It is a constant vector; Let be the covariance matrix of the clutter signal vector sequence; The weight coefficient matrix of the filter bank; This is the conjugate transpose.

7. The adaptive motion clutter suppression method based on filter banks according to claim 6, characterized in that, The weight coefficient matrix of the filter bank is: In the formula, The weighting coefficient vector for each pulse; The Doppler frequency for each filter; The pulse repetition period; ; This represents the number of filters.

8. The adaptive motion clutter suppression method based on filter banks according to claim 7, characterized in that, The calculation formula for performing the first noncoherent accumulation process on the canceled signal is as follows: In the formula, The output signal is the input signal after the cancellation process. , This represents the total number of pulses.

9. The adaptive motion clutter suppression method based on filter banks according to claim 8, characterized in that, The calculation formula for performing the second noncoherent accumulation process on the input signal is as follows: In the formula, For input signals; , This represents the total number of pulses.

10. A motion clutter adaptive suppression system based on filter banks, characterized in that, The system includes The filter design module is used to design a moving target display filter with a notch at zero frequency and to obtain the weight coefficient vector of the moving target display filter. The filter bank design module is used to translate the moving target display filter on the frequency axis to obtain the filter bank and the weight coefficient matrix of the filter bank; The calculation module is used to solve for the weight coefficient vector of the optimal filter based on the weight coefficient matrix; The cancellation processing module is used to cancel the input signal containing clutter and noise signals using the optimal filter; The noncoherent accumulation processing module is used to perform a first noncoherent accumulation processing on the signal after cancellation processing, and a second noncoherent accumulation processing on the input signal; The discrimination module is used to determine whether to output the results of the first noncoherent accumulation processing and the second noncoherent accumulation processing using clutter profile maps or target detection, and selects the output result based on the clutter profile map or target detection.

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