A frequency domain sliding extension cancellation method for external radiation source radar

Abstract

The application discloses an external radiation source radar frequency domain sliding expansion cancellation method and belongs to the field of digital signal processing. The application realizes the method as follows: overlapping segmentation is performed on a monitoring signal and a reference signal, and fast Fourier transform is performed; the strong correlation between the reference signal and multipath clutter at the same frequency point is utilized to suppress the static clutter at each frequency point in the bandwidth; the frequency domain signal after the static clutter suppression is transformed to the time domain, the overlapping part is removed, and the complete time domain signal after the clutter suppression is obtained; distance-Doppler two-dimensional matched filtering is performed, and moving clutter interference is detected, the moving clutter with different Doppler shifts is suppressed step by step, the filter order is always one order, the operation amount of the algorithm is significantly reduced, and the memory occupation is reduced. The application utilizes the principle of the external radiation source radar signal, can effectively suppress the interference of the moving clutter and the static clutter, is more easy to realize real-time processing of the signal, is not limited to the radiation source signal with a specific structure, and is more universal.

Description

Technical Field

[0001] This invention relates to a method for canceling the frequency domain sliding spread of an external radiation source radar, belonging to the field of digital signal processing. Background Technology

[0002] External source radar is a radar system that uses non-cooperative illumination sources (such as digital television broadcast signals) for target detection and tracking. Due to its advantages such as wide coverage, good concealment, low cost, and environmental friendliness, it has attracted widespread attention from researchers over the past few decades. The monitoring channel signals received by external source radar contain not only target echoes but also strong direct waves and multipath clutter. The target echo signal in the monitoring channel is often 60-100 dB lower than the clutter signal, and clutter sidelobes cause the target echo to be submerged in the echo spectrum. Therefore, clutter suppression is the most critical problem faced by external source radar.

[0003] Currently, clutter suppression methods for external radiation source radars are mainly divided into spatial domain and time domain clutter suppression methods. Spatial domain clutter suppression, by suppressing sidelobes and creating nulls, has a good suppression effect on sidelobe clutter, but it has no ability to suppress clutter within the main lobe. Commonly used time domain methods include the Wiener algorithm, recursive least squares algorithm, normalized least mean square algorithm, extended cancellation algorithm, batch extended cancellation algorithm, and sliding extended cancellation algorithm. These methods usually face the problem of high computational cost, especially for high sampling rate signals, making them difficult to apply in real-time signal processing.

[0004] To address the aforementioned issues, Clark applied the Fast Fourier Transform to the block least mean square algorithm, proposing a frequency-domain block adaptive filter that significantly improves the algorithm's computation speed. Zhuo proposed a clutter suppression method based on sub-band Wiener filters, which reduces the dimension of the Wiener filters in the sub-bands, thereby lowering computational complexity. In recent years, researchers have proposed carrier-domain cancellation methods based on the waveform characteristics of orthogonal frequency division multiplexing (OFDM) signals. These methods have the advantages of low computational cost and small memory footprint. However, carrier-domain algorithms rely on the demodulation and modulation of OFDM signals, which has some limitations. Summary of the Invention

[0005] The main objective of this invention is to provide a frequency domain sliding spread cancellation method for external radiation source radar. Utilizing the principles of external radiation source radar and digital signal processing technology, it achieves effective suppression of both dynamic and static clutter based on a sliding spread cancellation algorithm. This invention has advantages such as low computational complexity, small memory footprint, and good universality.

[0006] The objective of this invention is achieved through the following technical solution.

[0007] This invention discloses a frequency-domain sliding spread cancellation method for external radiation source radar. The method involves overlapping and segmenting the monitoring signal and reference signal, followed by a Fast Fourier Transform (FFT). Utilizing the strong correlation between the reference signal and multipath clutter at the same frequency point, static clutter at each frequency point within the bandwidth is suppressed. The frequency-domain signal after static clutter suppression is transformed to the time domain, and the overlapping portion is removed to obtain the complete time-domain signal after clutter suppression. Range-Doppler two-dimensional matched filtering is performed, and moving clutter interference is detected. Moving clutter with different Doppler frequency shifts is suppressed stepwise. This invention effectively suppresses interference from both moving and static clutter, has the advantages of low computational load and small memory footprint, is easier to implement in real-time signal processing, and is not limited to radiation source signals with specific structures, thus possessing greater universality.

[0008] This invention discloses a method for canceling the frequency domain sliding spread of an external radiation source radar, comprising the following steps:

[0009] Step 1: Perform quadrature demodulation and digital down-conversion processing on the monitoring signal and the reference signal to obtain the time-domain monitoring signal s(n) and the time-domain reference signal r(n).

[0010] The time-domain reference signal is represented as

[0011] r(n)=d(n) (1)

[0012] In the formula, d(n) represents the direct wave. Since the intensity of the direct wave is much higher than that of the noise, the influence of the noise is ignored.

[0013] Time-domain monitoring signal is represented as

[0014]

[0015] In the formula, N p For the number of static clutter; A p and n p Let N be the amplitude and time delay of the p-th static clutter, respectively; c For the number of moving clutter; A c n c f c The amplitude, time delay, and Doppler frequency of the c-th moving clutter are respectively; N t For the target quantity; A t n t f t f represents the amplitude, time delay, and Doppler frequency of the t-th target, respectively; s denoted as the sampling rate; z(n) represents the noise of the monitoring channel.

[0016] Step 2: Perform overlapping segmentation on the monitoring signal s(n) and reference signal r(n) obtained in Step 1.

[0017] The segmented m-th segment of the signal is represented as follows:

[0018]

[0019] In the formula, m = 1, 2, ..., M, N step N represents the step length for each segment. seg (N seg ≥2N del +N step ) represents the length of each segment, N del Let n = 1, 2, ..., N, be the target maximum time delay. seg When -1 / 2 ≤ x ≤ 1 / 2, rect(x) is 1, otherwise it is 0.

[0020] Step 3: Process the segmented monitoring signal s obtained in Step 2. m (n) Perform Fast Fourier Transform (FFT); for the segmented reference signal r obtained in step two... m (n) Perform FFT.

[0021] Step 3.1: For the segmented reference signal r m (n) Perform an FFT to obtain the corresponding frequency domain reference signal R. m (ω k Its expression is as follows:

[0022] R m (ω k ) = FFT[r m (n)]=FFT[d m [(n)]=D m (ω k (4)

[0023] In the formula, m = 1, 2, ..., M, d m (n) represents the m-th direct wave segment. For the data after FFT of the m-th direct wave segment, ω k =2πkf s / N seg k = 1, 2, ..., N seg N represents the frequency domain seg There are 1 sampling point, and the interval between the frequency domain sampling points is Δf = f. s / N seg .

[0024] Step 3.2: Process the segmented monitoring signal s m (n) Perform an FFT to obtain the corresponding frequency domain monitoring signal S. m (ω k Its expression is as follows:

[0025]

[0026] In the formula, m = 1, 2, ..., M, Z m (ω k ) represents the noise of the m-th frequency domain monitoring signal.

[0027] The FFT representation of the p-th static clutter is as follows.

[0028]

[0029] The FFT representation of the c-th moving clutter is as follows.

[0030]

[0031] In the formula, the interval Δf between frequency domain sampling points is greater than the Doppler frequency of the target or clutter, i.e., ω k ≈ω k ±2πf c Therefore, formula (7) is expressed as follows:

[0032]

[0033] Similarly, the FFT representation of the t-th target echo is as follows:

[0034]

[0035] Substituting formulas (6), (8), and (9) into (5), we get:

[0036]

[0037] Step 4: Using the frequency domain monitoring signal and frequency domain reference signal obtained in Step 3, suppress the clutter at each frequency point within the bandwidth, set the coefficient of the noise frequency point to zero, and obtain the frequency domain signal after clutter suppression.

[0038] Step 4.1 Extract the effective frequency points from the frequency domain signal.

[0039] Frequency points within the signal bandwidth are called effective frequency points, and frequency points outside the signal bandwidth are called noise frequency points. Let the number of effective frequency points of the signal be N. b Then the index set corresponding to the effective frequency points is:

[0040]

[0041] The expression for the reference signal at the k-th frequency point is:

[0042] R k =D k (12)

[0043] In the formula, k∈I, D k =[D 1,k ,…D m,k ,…D M,k ] T This is the expression for the k-th frequency point of the direct wave;

[0044] The expression for the monitoring signal at the k-th frequency point is:

[0045]

[0046] In the formula, k∈I, Okay, R k With X k and Y k The correlation is very small; if f c ≠f t Then X k With Y k Almost uncorrelated; and noise Z k With R k X k and Y k None of them are relevant.

[0047] Step 4.2 Divide the reference signal and monitoring signal at the k-th (k∈I) frequency point into B blocks, each block having a length of M. B =M / B. Based on this, each reference signal and monitoring signal is shifted backward and forward by an additional M. S / 2 points are used as sliding windows.

[0048] The monitoring signal for block b (b = 0, 1, ..., B-1) is:

[0049]

[0050] The reference signal for the b-th block (b = 0, 1, ..., B-1) is:

[0051]

[0052] Step 4.3 Construct the static clutter subspace matrix.

[0053]

[0054] Step 4.4 Filter each monitoring signal separately, for the b-th monitoring signal. Projected onto X b Orthogonal subspaces yield the canceled signal.

[0055]

[0056] In the formula, b = 0, 1, ..., B-1, It is X b The conjugate transpose of .

[0057] Step 4.5 After canceling the clutter at each effective frequency point, the coefficients at the noise frequency points are set to zero to obtain the frequency domain signal after suppressing the noise.

[0058]

[0059] Step 5: Using the frequency domain signal with suppressed static clutter obtained in Step 4, perform an Inverse Fast Fourier Transform (IFFT) to remove the overlapping parts and obtain the complete time domain signal with suppressed static clutter.

[0060] Step 5.1 Perform IFFT on the frequency domain signal after suppressing static clutter.

[0061] The frequency domain signal after noise suppression is:

[0062]

[0063] For the m-th (m=1,2,...,M) segment of the signal, i.e. the m-th row vector in equation (19), the expression for IFFT is:

[0064]

[0065] Step 5.2 Remove the overlapping parts and obtain the complete time-domain signal after suppressing static clutter.

[0066]

[0067] Step 6: Using the time-domain monitoring signal o(n) obtained in Step 5 and the time-domain reference signal r(n) obtained in Step 1, perform range-Doppler two-dimensional matched filtering to obtain the matched filtering result.

[0068] Step 7: Using the matched filtering results obtained in Step 6, detect whether there is dynamic clutter interference; if there is no dynamic clutter interference, end the cancellation; if there is dynamic clutter interference, save the dynamic clutter Doppler information and execute Steps 8, 9 and 10.

[0069] Step 8: Using the static clutter subspace matrix obtained in Step 4 and the dynamic clutter Doppler information obtained in Step 7, and utilizing the strong correlation of clutter with the same Doppler frequency shift at the same frequency point, establish the dynamic clutter subspace corresponding to the Doppler frequency shift.

[0070] The dynamic clutter subspace is:

[0071]

[0072] In the formula, k (k∈I) is the kth frequency point, f q (q=1,2,...,Q) represents the Doppler frequencies of the dynamic clutter, and Q represents the number of different Doppler frequencies.

[0073] Step 9: Utilize the frequency domain signal obtained in Step 4 after suppressing static clutter. and the dynamic clutter subspace obtained in step eight For each dynamic clutter subspace Clutter cancellation is performed to ensure that the filter order remains at first order.

[0074] Step 9.1 Let q = 1, and convert the frequency domain signal... Projected onto Orthogonal subspaces yield the canceled signal.

[0075]

[0076] In the formula, b = 0, 1, ..., B-1.

[0077] Step 9.2 If q = Q, then Otherwise, q = q + 1, which represents the frequency domain signal. Projected onto Orthogonal subspaces yield new canceled signals

[0078]

[0079] Step 9.3 If q ≠ Q, then return to step 9.2. Otherwise,

[0080] Step 10: Using the frequency domain signal obtained in Step 9 after suppressing dynamic clutter, perform IFFT to remove the overlapping parts and obtain the complete time domain signal after suppressing dynamic clutter, thus achieving effective suppression of dynamic and static clutter.

[0081] Beneficial effects:

[0082] 1. The present invention discloses a frequency domain sliding spread cancellation method for external radiation source radar, which utilizes the strong correlation between the reference signal and multipath clutter at the same frequency point, and the lack of correlation between moving clutter and the echo signal of moving target at the same frequency point, to achieve effective suppression of moving and static clutter.

[0083] 2. The present invention discloses a frequency domain sliding spread cancellation method for external radiation source radar. It utilizes the strong correlation of clutter with the same Doppler frequency shift at the same frequency point to establish a corresponding dynamic clutter subspace. Clutter cancellation is performed on each dynamic clutter subspace, so that the filter order is always first order, which significantly reduces the computational load of the algorithm and reduces the memory footprint.

[0084] 3. The present invention discloses a frequency domain sliding spread cancellation method for external radiation source radar. It utilizes external radiation source radar signal processing technology to perform FFT on the overlapping segmented signal and suppress clutter at each frequency point within the bandwidth. The present invention is not limited to radiation source signals with specific structures and has greater universality. Attached Figure Description

[0085] Figure 1 This is a flowchart of the static clutter suppression method in an embodiment of the present invention, "A method for canceling frequency domain sliding spread of an external radiation source radar".

[0086] Figure 2 This is a flowchart of the dynamic clutter suppression method in an embodiment of the present invention, "A Method for Cancelling Frequency Domain Sliding Spread of External Radar Sources".

[0087] Figure 3 This is a schematic diagram of signal overlap segmentation in an embodiment of the present invention, "A method for canceling frequency domain sliding spread of an external radiation source radar".

[0088] Figure 4 This is a schematic diagram of the frequency domain sliding spread cancellation algorithm in an embodiment of the present invention, "A method for canceling frequency domain spread of an external radiation source radar".

[0089] Figure 5 This is the range-Doppler two-dimensional matched filtering result before clutter suppression in the embodiment of the present invention, "A method for canceling the frequency domain sliding spread of an external radiation source radar".

[0090] Figure 6 This is the range-Doppler two-dimensional matched filtering result after static clutter suppression in the embodiment of the present invention, "A method for canceling frequency domain sliding spread of external radiation source radar".

[0091] Figure 7 This is the range-Doppler two-dimensional matched filtering result after suppressing dynamic and static clutter in the embodiment of the present invention, "A method for canceling frequency domain sliding spread of external radiation source radar".

[0092] Figure 8 This is a comparison diagram of the signal-to-clutter ratio of target 1 in the Doppler domain in an embodiment of the present invention, "A method for canceling frequency domain extension of external radiation source radar".

[0093] Figure 9This is a comparison chart of the signal-to-clutter ratio of target 2 in the Doppler domain in an embodiment of the present invention, "A method for canceling frequency domain extension of external radiation source radar". Detailed Implementation

[0094] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific examples. It should be noted that the described embodiments are only intended to facilitate the understanding of the present invention and do not serve any limiting purpose.

[0095] In this embodiment of the invention, the signal is a single-carrier mode digital television terrestrial broadcasting (DTTB) signal with a bandwidth of 7.56MHz and a receiving end sampling rate of 9MHz.

[0096] like Figure 1 and 2 As shown in the figure, the specific implementation steps of the frequency domain sliding spread cancellation method for external radiation source radar disclosed in this embodiment are as follows:

[0097] Step 1: Perform quadrature demodulation and digital down-conversion processing on the monitoring signal and the reference signal to obtain the time-domain monitoring signal s(n) and the time-domain reference signal r(n).

[0098] The time-domain reference signal is represented as follows:

[0099] r(n)=d(n) (1)

[0100] In the formula, d(n) represents the direct wave. Since the intensity of the direct wave is much higher than that of the noise, the influence of the noise is ignored.

[0101] The time-domain monitoring signal is represented as follows:

[0102]

[0103] In the formula, N p For the number of static clutter; A p and n p Let N be the amplitude and time delay of the p-th static clutter, respectively; c For the number of moving clutter; A c n c f c The amplitude, time delay, and Doppler frequency of the c-th moving clutter are respectively; N t For the target quantity; A t n t f t f represents the amplitude, time delay, and Doppler frequency of the t-th target, respectively; s denoted as the sampling rate; z(n) represents the noise of the monitoring channel.

[0104] Step 2: Perform overlapping segmentation on the monitoring signal s(n) and reference signal r(n) obtained in Step 1. A segmentation diagram is shown below. Figure 3 As shown. The m-th segment of the signal after segmentation is represented as follows:

[0105]

[0106] In the formula, m = 1, 2, ..., M, N step N represents the step length for each segment. seg (N seg ≥2N del +N step ) represents the length of each segment, N del Let n = 1, 2, ..., N, be the target maximum time delay. seg When -1 / 2 ≤ x ≤ 1 / 2, rect(x) is 1; otherwise, it is 0. The signal segmentation parameters are shown in Table 1.

[0107] Table 1 Signal Segmentation Parameters

[0108]

[0109] Step 3: Process the segmented monitoring signal s obtained in Step 2. m (n) Perform FFT on the segmented reference signal r obtained in step two; m (n) Perform FFT.

[0110] Step 3.1: For the segmented reference signal r m (n) Perform an FFT to obtain the corresponding frequency domain reference signal R. m (ω k Its expression is as follows:

[0111] R m (ω k ) = FFT[r m (n)]=FFT[d m [(n)]=D m (ω k (4)

[0112] In the formula, m = 1, 2, ..., M, d m (n) represents the m-th direct wave segment. For the data after FFT of the m-th direct wave segment, ω k =2πkf s / N seg k = 1, 2, ..., N seg N represents the frequency domain seg There are 1 sampling point, and the interval between the frequency sampling points is Δf = f. s / N seg .

[0113] Step 3.2: Process the segmented monitoring signal s m (n) Perform an FFT to obtain the corresponding frequency domain monitoring signal S. m (ω k Its expression is as follows:

[0114]

[0115] In the formula, m = 1, 2, ..., M, Z m (ω k ) represents the noise of the m-th frequency domain monitoring signal.

[0116] The FFT representation of the p-th static clutter is as follows.

[0117]

[0118] The FFT representation of the c-th moving clutter is as follows.

[0119]

[0120] In the formula, the interval Δf between frequency domain sampling points is greater than the Doppler frequency of the target or clutter, i.e., ω k ≈ω k ±2πf c Therefore, formula (7) is expressed as follows:

[0121]

[0122] Similarly, the FFT representation of the t-th target echo is as follows:

[0123]

[0124] Substituting formulas (6), (8), and (9) into (5), we get:

[0125]

[0126] Step 4: Using the frequency domain monitoring signal and frequency domain reference signal obtained in Step 3, suppress clutter at each frequency point within the bandwidth, setting the coefficients at noise frequency points to zero to obtain the clutter-suppressed frequency domain signal. A schematic diagram of the frequency domain sliding spread cancellation algorithm is shown below. Figure 4 As shown in Table 2, the input parameters for cancellation are as follows.

[0127] Table 2 Frequency Domain Sliding Spread Cancellation Input Parameters

[0128]

[0129] Step 4.1 Extract the effective frequency points from the frequency domain signal.

[0130] Frequency points within the signal bandwidth are called effective frequency points, and frequency points outside the signal bandwidth are called noise frequency points. Let the number of effective frequency points of the signal be N. b Then the index set corresponding to the effective frequency points is:

[0131]

[0132] The expression for the reference signal at the k-th frequency point is:

[0133] R k =D k (12)

[0134] In the formula, k∈I, D k =[D 1,k ,…D m,k ,…D M,k ] T This is the expression for the k-th frequency point of the direct wave;

[0135] The expression for the monitoring signal at the k-th frequency point is:

[0136]

[0137] In the formula, k∈I, Okay, R k With X k and Y k The correlation is very small; if f c ≠f t Then X k With Y k Almost uncorrelated; and noise Z k With R k X k and Y k None of them are relevant.

[0138] Step 4.2 Divide the reference signal and monitoring signal at the k-th (k∈I) frequency point into B blocks, each block having a length of M. B =M / B. Based on this, each reference signal and monitoring signal is shifted backward and forward by an additional M. S / 2 points are used as sliding windows.

[0139] The monitoring signal for block b (b = 0, 1, ..., B-1) is:

[0140]

[0141] The reference signal for the b-th block (b = 0, 1, ..., B-1) is:

[0142]

[0143] Step 4.3 Construct the static clutter subspace matrix.

[0144]

[0145] Step 4.4 Filter each monitoring signal separately, for the b-th monitoring signal. Projected onto X b Orthogonal subspaces yield the canceled signal.

[0146]

[0147] In the formula, b = 0, 1, ..., B-1, It is X b The conjugate transpose of .

[0148] Step 4.5 After canceling the clutter at each effective frequency point, the coefficients at the noise frequency points are set to zero to obtain the frequency domain signal after suppressing the noise.

[0149]

[0150] Step 5: Using the frequency domain signal with suppressed static clutter obtained in Step 4, perform IFFT to remove the overlapping parts and obtain the complete time domain signal with suppressed static clutter.

[0151] Step 5.1 Perform IFFT on the frequency domain signal after suppressing static clutter.

[0152] The frequency domain signal after noise suppression is:

[0153]

[0154] For the m-th (m=1,2,...,M) segment of the signal, i.e. the m-th row vector in equation (19), the expression for IFFT is:

[0155]

[0156] Step 5.2 Remove the overlapping parts and obtain the complete time-domain signal after suppressing static clutter.

[0157]

[0158] Step 6: Using the time-domain monitoring signal o(n) obtained in Step 5 and the time-domain reference signal r(n) obtained in Step 1, perform range-Doppler two-dimensional matched filtering to obtain the matched filtering result.

[0159] Matched filtering results before clutter suppression are as follows Figure 5As shown in the figure, multipath clutter at and near zero frequency is most prominent, completely obscuring the target. The matched filtering result after suppressing the static clutter using the frequency domain sliding spread cancellation algorithm is as follows: Figure 6 As shown in the figure, both targets can be detected. Most of the zero-frequency and near-zero-frequency clutter has been canceled out, but there is still strong non-zero-frequency clutter near the targets.

[0160] Step 7: Using the matched filtering results obtained in Step 6, detect whether there is dynamic clutter interference; if there is no dynamic clutter interference, end the cancellation; if there is dynamic clutter interference, save the dynamic clutter Doppler information and execute Steps 8, 9 and 10.

[0161] Step 8: Using the static clutter subspace matrix obtained in Step 4 and the dynamic clutter Doppler information obtained in Step 7, and utilizing the strong correlation of clutter with the same Doppler frequency shift at the same frequency point, establish the dynamic clutter subspace corresponding to the Doppler frequency shift.

[0162] The dynamic clutter subspace is:

[0163]

[0164] In the formula, k (k∈I) is the kth frequency point, f q (q=1,2,...,Q) represents the Doppler frequencies of the dynamic clutter, and Q represents the number of different Doppler frequencies.

[0165] Step 9: Utilize the frequency domain signal obtained in Step 4 after suppressing static clutter. and the dynamic clutter subspace obtained in step eight For each dynamic clutter subspace Clutter cancellation is performed to ensure that the filter order remains at first order.

[0166] Step 9.1 Let q = 1, and convert the frequency domain signal... Projected onto Orthogonal subspaces yield the canceled signal.

[0167]

[0168] In the formula, b = 0, 1, ..., B-1.

[0169] Step 9.2 If q = Q, then Otherwise, q = q + 1, which represents the frequency domain signal. Projected onto Orthogonal subspaces yield new canceled signals

[0170]

[0171] Step 9.3 If q ≠ Q, then return to step 9.2. Otherwise,

[0172] Step 10: Using the frequency domain signal with suppressed dynamic clutter obtained in Step 9, perform IFFT to remove the overlapping parts and obtain the complete time domain signal with suppressed dynamic clutter.

[0173] against Figure 6 For relatively strong dynamic clutter, a corresponding clutter subspace is established. The distance-Doppler two-dimensional matched filter result after dynamic clutter cancellation is as follows: Figure 7 As shown in the figure, clutter near the target has been effectively suppressed. To further analyze the performance of the cancellation algorithm, Figure 8 and 9 The figures show a comparison of the signal-to-clutter ratio (SNR) for target 1 and target 2 in the Doppler domain. Table 3 also provides the corresponding SNR values. Combining the figures and tables, it is clear that after suppressing the moving clutter, the SNR is improved by nearly 3 dB. This indicates that the proposed method can significantly improve the SNR of the target after suppressing the moving clutter.

[0174] Table 3. Signal-to-noise ratio after clutter suppression

[0175]

[0176] The above detailed description further illustrates the purpose, technical solution, and beneficial effects of the invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for canceling the frequency domain sliding spread of an external radiation source radar, characterized in that: Includes the following steps, Step 1: Perform quadrature demodulation and digital down-conversion processing on the monitoring signal and the reference signal to obtain the time-domain monitoring signal. and time-domain reference signal ; Step 2: Process the monitoring signals obtained in Step 1 and reference signal Perform overlapping segmentation processing; Step 3: Process the segmented monitoring signals obtained in Step 2. Perform a Fast Fourier Transform (FFT); on the segmented reference signal obtained in step two... Perform FFT; Step 4: Using the frequency domain monitoring signal and frequency domain reference signal obtained in Step 3, suppress the clutter at each frequency point within the bandwidth, set the coefficient of the noise frequency point to zero, and obtain the frequency domain signal after clutter suppression. Step 5: Using the frequency domain signal with suppressed static clutter obtained in Step 4, perform an inverse fast Fourier transform (IFFT) to remove the overlapping parts and obtain the complete time domain signal with suppressed static clutter. Step 6: Utilize the time-domain monitoring signal obtained in Step 5 and the time-domain reference signal obtained in step one Perform a two-dimensional matched filter with distance-Doppler to obtain the matched filter result; Step 7: Using the matched filtering results obtained in Step 6, detect whether there is dynamic clutter interference; if there is no dynamic clutter interference, end the cancellation; if there is dynamic clutter interference, save the dynamic clutter Doppler information and execute Steps 8, 9 and 10. Step 8: Using the static clutter subspace matrix obtained in Step 4 and the dynamic clutter Doppler information obtained in Step 7, and utilizing the strong correlation of clutter with the same Doppler frequency shift at the same frequency point, establish the dynamic clutter subspace corresponding to the Doppler frequency shift. Step 9: Utilize the frequency domain signal obtained in Step 4 after suppressing static clutter. and the dynamic clutter subspace obtained in step eight ,in , For each dynamic clutter subspace Clutter cancellation is performed to ensure that the filter order is always first order. Step 10: Using the frequency domain signal obtained in Step 9 after suppressing dynamic clutter, perform IFFT to remove the overlapping parts and obtain the complete time domain signal after suppressing dynamic clutter, thus achieving effective suppression of dynamic and static clutter.

2. The frequency domain sliding spread cancellation method for external radiation source radar as described in claim 1, characterized in that: In step one, the time-domain reference signal is represented as: （1） In the formula, This is a direct wave; since the intensity of the direct wave is much higher than that of the noise, the effect of the noise is ignored. Time-domain monitoring signal is represented as （2） In the formula, This represents the number of static clutter waves; and The first The amplitude and time delay of the static clutter; The number of moving clutter; , , The first The amplitude, time delay, and Doppler frequency of individual dynamic clutter; For the target quantity; , , The first The amplitude, delay, and Doppler frequency of each target; Sampling rate; To monitor channel noise.

3. The frequency domain sliding spread cancellation method for external radiation source radar as described in claim 2, characterized in that: In step two, The segmented first The segment signal is represented as: （3） In the formula, , The step length for each segment, The length of each segment is , where , For the target maximum latency, ,when hour, It is 1 if it is true, otherwise it is 0.

4. The frequency domain sliding spread cancellation method for external radiation source radar as described in claim 3, characterized in that: The method for implementing step three is as follows: Step 3.1: For the segmented reference signal Perform an FFT to obtain the corresponding frequency domain reference signal. Its expression is as follows: （4） In the formula, , For the first Direct wave segment For the first The data after FFT of the direct wave segment, , Representing the frequency domain There are sampling points, and the interval between frequency domain sampling points is . ; Step 3.2: Process the segmented monitoring signals Perform an FFT to obtain the corresponding frequency domain monitoring signal. Its expression is as follows: （5） In the formula, , For the first Noise in the frequency domain monitoring signal; For the first The FFT representation of a static clutter wave is as follows. （6） For the first The dynamic clutter is represented by the following FFT: （7） In the formula, the interval between frequency domain sampling points The Doppler frequency is greater than that of the target or clutter, i.e. Therefore, formula (7) is expressed as follows: （8） Same as above, for the first The target echo is represented by FFT as follows. （9） Substituting formulas (6), (8), and (9) into (5), we get: （10）。 5. The frequency domain sliding spread cancellation method for external radiation source radar as described in claim 4, characterized in that: Step four is implemented as follows: Step 4.1 Extract the effective frequency points from the frequency domain signal; Frequency points within the signal bandwidth are called effective frequency points, and frequency points outside the signal bandwidth are called noise frequency points; let the number of effective frequency points of the signal be... The index set corresponding to the effective frequency points is: （11） The reference signal is at the The expression for each frequency point is: （12） In the formula, , For the direct wave The expression for each frequency point; The monitoring signal is at the The expression for each frequency point is: （13） In the formula, , , ; have to, and and The correlation is very small; if ,but and Almost unrelated; and noise and , and None of them are relevant; Step 4.2 The first The reference signal and monitoring signal at each frequency point are divided into Block, in which Each piece is [length] Based on this, each reference signal and monitoring signal is taken both backward and forward. Each point serves as a sliding window; No. The monitoring signal for the block is: （14） No. The reference signal for the block is: （15） ； Step 4.3 Construct the static clutter subspace matrix; （16） Step 4.4 Filter each monitoring signal separately. Block monitoring signal Projected onto Orthogonal subspaces yield the canceled signal. ; （17） In the formula, , yes The conjugate transpose of; Step 4.5 After canceling the clutter at each effective frequency point, set the coefficients at the noise frequency points to zero to obtain the frequency domain signal after suppressing the static clutter. ; （18）。 6. The frequency domain sliding spread cancellation method for external radiation source radar as described in claim 5, characterized in that: Step five is implemented as follows: Step 5.1 Perform IFFT on the frequency domain signal after noise suppression; The frequency domain signal after noise suppression is: （19） For the segment signal, That is, the first in equation (19) The expression for performing an IFFT on a row vector is: （20） Step 5.2 Remove the overlapping parts and obtain the complete time-domain signal after suppressing static clutter; （21）。 7. The frequency domain sliding spread cancellation method for an external radiation source radar as described in claim 6, characterized in that: In step six, the dynamic clutter subspace is: （22） In the formula, For the first Each frequency point, , The Doppler frequency of the dynamic clutter. , For different Doppler frequencies.

8. The frequency domain sliding spread cancellation method for an external radiation source radar as described in claim 7, characterized in that: Step nine is implemented as follows: Step 9.1 Let frequency domain signal Projected onto Orthogonal subspaces yield the canceled signal. ; （23） In the formula, ; Step 9.2 If ,but ; otherwise, frequency domain signal Projected onto Orthogonal subspaces yield new canceled signals ; （24） Step 9.3 If If yes, then return to step 9.2; otherwise, .

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