A slice interference positioning and suppression method based on integral decomposition

Abstract

The application discloses a slice interference positioning and suppression method based on integral decomposition, which comprises the following steps: receiving an original echo signal and performing pulse compression on the original echo signal; the original echo signal contains a plurality of target signals, the plurality of target signals contain real target signals and false target signals, and the false target signals are interference signals; detecting the peak position of each target signal from the echo signal after pulse compression; for each target signal, integral decomposition is performed on the original echo signal based on the peak position of the signal to obtain the integral decomposition result of the signal; the positions of each real target signal and each interference signal in the time-frequency domain are determined based on the integral decomposition result; an interference suppression filter is constructed based on the positions of the real target signals and the interference signals in the time-frequency domain; the original echo signal is subjected to short-time Fourier transform, and the signal after the short-time Fourier transform is filtered by using the interference suppression filter. The application can improve the interference suppression ratio, thereby improving the interference suppression effect.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of radar, and particularly relates to a slice jamming positioning and suppression method based on integral decomposition. BACKGROUND

[0002] In a modern radar electronic warfare system, with the development of digital radio frequency memory technology, a jammer can flexibly set slice jamming parameters, so that the jamming can produce various false targets on an RD diagram. Since slice jamming can obtain matched filtering and coherent processing gain, its jamming effect is obvious, so that target detection in a slice jamming environment becomes very difficult. Therefore, in order to improve the anti-jamming capability of a radar, the echo signal is usually mapped to a higher dimension, the feature difference between slice jamming and a signal is mined, and a filter is constructed to filter out jamming, so as to retain a real target signal, so that the radar can detect the real target.

[0003] The jamming suppression method of the traditional scheme generally uses short-time Fourier transform to map the echo signal to a time-frequency domain, uses the energy difference between a target signal and jamming to obtain a jamming positioning result, and then suppresses the jamming. However, since the jammer modulation is flexible, a jamming decision threshold is difficult to obtain. Meanwhile, the grating lobes introduced by the tailing phenomenon of jamming edges in the time-frequency domain are difficult to be positioned and suppressed, so that the final jamming suppression effect is poor.

[0004] That is, when the traditional scheme is used for jamming suppression, the time-frequency diagram energy segmentation threshold is difficult to obtain, a large signal loss or a low jamming suppression ratio is caused at a low signal-to-jamming ratio, and the jamming grating lobes introduced by the tailing in the time-frequency domain are difficult to be suppressed, so that the jamming suppression ratio is difficult to improve, and finally the jamming suppression effect is poor. SUMMARY

[0005] In order to solve the above problems in the prior art, the application provides a slice jamming positioning and suppression method based on integral decomposition.

[0006] The technical problem to be solved by the application is solved by the following technical scheme:

[0007] The application provides a slice jamming positioning and suppression method based on integral decomposition, which comprises the following steps:

[0008] An original echo signal is received, and pulse compression is performed on the original echo signal to obtain a pulse-compressed echo signal; the original echo signal comprises a plurality of target signals, and the plurality of target signals comprise a real target signal and a false target signal, wherein one false target signal is one jamming signal;

[0009] The peak position of each target signal in the plurality of target signals is detected from the pulse-compressed echo signal;

[0010] for each target signal, based on a peak position of the target signal, performing integral decomposition on the original echo signal to obtain an integral decomposition result of the target signal;

[0011] based on the integral decomposition results of the plurality of target signals, determining a time-frequency domain position of each real target signal and each interference signal;

[0012] based on the time-frequency domain positions of all real target signals and all interference signals in the plurality of target signals, constructing an interference suppression filter;

[0013] performing short-time Fourier transform on the original echo signal to obtain a time-frequency domain echo signal;

[0014] filtering the time-frequency domain echo signal by using the interference suppression filter to obtain a filtered time-frequency domain echo signal.

[0015] Compared with the prior art, the present application has the following beneficial effects:

[0016] The present application analyzes the characteristic differences between signals and interference by the method of integral decomposition, and obtains the positions of target signals and interference signals in the time-frequency domain according to the calculation of the integral decomposition results. A special form of time-frequency domain filter is designed according to the positions of target and interference in the time-frequency domain, which can protect the target signal, suppress the interference, and effectively filter out the tailing of the interference edge in the time-frequency domain. The problem that the energy segmentation threshold is difficult to determine in the traditional time-frequency domain filtering algorithm is effectively avoided, the interference suppression ratio is improved, the loss of the signal in the anti-interference process is reduced, and the interference suppression effect is improved, so that the radar can accurately identify and detect the real target, and the anti-interference ability of the modern radar in the complex electromagnetic environment is improved.

[0017] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a flowchart of a slice interference positioning and suppression method based on integral decomposition provided by an embodiment of the present application;

[0019] Figure 2 is a comparison diagram of the amplitude variation curve of a real target signal and the amplitude variation curve linearly fitted by an embodiment of the present application;

[0020] Figure 3 is a difference result diagram between the amplitude variation curve of an interference signal and the amplitude variation curve linearly fitted by the interference signal according to an embodiment of the present application;

[0021] Figure 4is a time-frequency diagram of the original echo signal provided by the embodiment of the present application;

[0022] Figure 5 is a schematic diagram of the constructed interference suppression filter provided by the embodiment of the present application;

[0023] Figure 6 is a comparison schematic diagram of the interference signal before and after being covered up provided by the embodiment of the present application;

[0024] Figure 7 is a schematic diagram of the filtered time-frequency domain echo signal obtained after the time-frequency domain echo signal is filtered by the interference suppression filter of the present application;

[0025] Figure 8 is a comparison diagram of the coherent accumulation results before and after the interference suppression is performed by the method of the present application. DETAILED DESCRIPTION

[0026] The present application will be further described in detail below in combination with specific embodiments, but the embodiments of the present application are not limited thereto.

[0027] Figure 1 is a flowchart of a slice interference positioning and suppression method based on integral decomposition provided by the embodiment of the present application, as shown in Figure 1 , the method comprises:

[0028] S101, receiving an original echo signal, and performing pulse compression on the original echo signal to obtain a pulse-compressed echo signal; the original echo signal contains a plurality of target signals, and the plurality of target signals contain real target signals and false target signals, wherein one false target signal is one interference signal.

[0029] S102, detecting the peak position of each target signal in the plurality of target signals from the pulse-compressed echo signal.

[0030] S103, for each target signal, based on the peak position of the target signal, performing integral decomposition on the original echo signal to obtain the integral decomposition result of the target signal.

[0031] S104, based on the integral decomposition results of the plurality of target signals, determining the position in the time-frequency domain of each real target signal and each interference signal.

[0032] S105, based on the positions in the time-frequency domain of all real target signals and all interference signals in the plurality of target signals, constructing an interference suppression filter.

[0033] S106, performing short-time Fourier transform on the original echo signal to obtain a time-frequency domain echo signal.

[0034] S107, filtering the time-frequency domain echo signal by using the interference suppression filter to obtain a filtered time-frequency domain echo signal.

[0035] The application analyzes the characteristic difference between the signal and the interference by the integral decomposition method, obtains the positions of the target signal and the interference signal in the time-frequency domain according to the calculation of the integral decomposition result, and designs a special form of time-frequency domain filter according to the positions of the target and the interference in the time-frequency domain, so that the target signal can be protected, the interference can be suppressed, and the tailing of the interference edge in the time-frequency domain can be effectively filtered out. The problem that the energy segmentation threshold of the traditional time-frequency domain filtering algorithm is difficult to determine is effectively avoided, the interference suppression ratio is improved, the loss of the signal in the anti-interference process is reduced, and then the interference suppression effect is improved, so that the radar can accurately identify and detect the real target, and the anti-interference ability of the modern radar in the complex electromagnetic environment is improved.

[0036] In some embodiments, after S107 described above, the method further includes S108:

[0037] S108, performing inverse short-time Fourier transform on the filtered time-frequency domain echo signal to obtain a time domain echo signal after interference suppression.

[0038] For S101 described above, the original echo signal is received by the radar, and the received signal is a discrete signal. For example, the original echo signal received by the radar is represented as: r (t)=s t (t)+s j (t)+n(t), wherein s r (t) is the original echo signal received by the radar, s t (t) is the target echo signal, s j (t) is the interference signal, and n(t) is the noise signal.

[0039] For S102 described above, the CFAR detection method can be specifically used to detect the peak position of each target signal from the pulse pressure echo signal. The purpose of the CFAR detection is to detect the target position in the noise, and the basic principle is to compare the energy of the detection unit x and the energy of the reference units on both sides. When the reference threshold level is exceeded, it is determined that the point exists target.

[0040] In the application, S103 described above can be specifically implemented as follows: taking the peak position of the target signal as the center, selecting a signal with a length of T p from the original echo signal, and multiplying the selected signal with the complex conjugate of the radar transmitting signal to obtain the integral decomposition result of the target signal, wherein T p is the pulse width of the radar transmitting signal.

[0041] For example, the integral decomposition result of a target signal can be expressed as:

[0042] ID(k)=s r (p-T p / 2+k)·s ref (k),k=1,2,...,T p ;

[0043] wherein, p represents the peak position of the target signal, s r (p-T p / 2+k) represents a signal of a preset length T p centered at p selected from the original echo signal, the integral decomposition result of the target signal is T p amplitudes, ID(k) represents the kth amplitude in the integral decomposition result of the target signal, s ref (k) represents the complex conjugate of the radar transmitting signal, s ref (k) is the reference signal.

[0044] In the present application, the above S104 is realized by the following steps:

[0045] S1041, identifying real target signals and interference signals from the multiple target signals according to the integral decomposition results of the multiple target signals.

[0046] Specifically, for each target signal, the integral decomposition result of the target signal contains multiple amplitudes, the multiple amplitudes in the integral decomposition result of the target signal can be added first to obtain an amplitude variation curve of the target signal, wherein the amplitude variation curve is formed by a set of values obtained by the addition processing; and the amplitude variation curve of the target signal is linearly fitted once to obtain a fitted amplitude variation curve of the target signal; then, the similarity between the amplitude variation curve of the target signal and the fitted amplitude variation curve is calculated to obtain a similarity value; when the similarity value is greater than or equal to a preset threshold, it indicates that the target signal is a real target signal, and when the similarity value is less than the preset threshold, it indicates that the target signal is an interference signal.

[0047] Specifically, the principle expression of the above addition processing of the multiple amplitudes in the integral decomposition result of the target signal is as follows:

[0048]

[0049] wherein, M=T p, P(m) represents the mth value in a set of values ​​forming the amplitude change curve of the target signal, and the set of values ​​forming the amplitude change curve of the target signal is: P(1), P(2), P(3),..., P(M).

[0050] For example, Figure 2 Figure (a) is a comparison of the amplitude change curve of a real target signal and the amplitude change curve obtained by a linear fitting. Figure 2 Figure (b) is a comparison of the amplitude variation curve of a slice interference signal and the amplitude variation curve obtained by linear fitting. For the real target peak, in the entire pulse width T p During the duration, each point of the target signal can obtain the matched filter gain, so P(m) continues to rise, such as Figure 2 As shown by the red line in Figure (a); for the false target peak (i.e., the interference target peak), since the slice interference signal is short in duration or discontinuous, P(m) shows an intermittent rise, as shown in Figure 2 As shown by the blue line in Figure (b). Therefore, the present invention performs a linear fitting on the energy distribution curve (i.e., the amplitude change curve), and the fitting result of the real target peak is as follows: Figure 2 The red line in (b) of the figure shows that the interference signal peak is as shown in Figure 2 As shown by the blue line in Figure (b), by calculating the similarity between the energy distribution curve and the curve obtained by linear fitting, the judgment threshold can be set. By setting the judgment threshold and similarity, the target signal and the interference signal can be accurately classified.

[0051] S1042, the pulse width T of the radar transmission signal p as the pulse width of each real target signal.

[0052] S1043. For each identified interference signal, determine the pulse width T of the interference signal in the time domain according to the integral decomposition result of the interference signal. jam ; Among them, the pulse width T of the interference signal in the time domain jam is a minimum value Δ min With a maximum value Δ max The absolute value of the difference, that is, T jam =Δ max -Δ min .

[0053] Specifically, the amplitude variation curve of the interference signal can be differentiated from the fitted amplitude variation curve of the interference signal to obtain a maximum difference point and a minimum difference point; then, the abscissa of the maximum difference point is used as the maximum value Δ max , the horizontal coordinate of the minimum difference point is taken as the minimum value Δ min ; Afterwards, calculate the minimum value Δmin With the maximum value Δ max The absolute value of the difference between the two is taken as the pulse width T of the interference signal in the time domain. jam .

[0054] For example, Figure 3 This is the difference result between the amplitude change curve of an interference signal and the amplitude change curve obtained by linear fitting of the interference signal. Figure 3 As shown in the figure, by differentiating the two curves, we can get a maximum difference point (201, 278.83) and a minimum difference point (50, -42.588). The horizontal coordinate Δ of the maximum difference point (201, 278.83) max and the horizontal coordinate Δ of the minimum difference point (50, -42.588) min , respectively corresponding to the starting point and end point of the time domain position of the interference signal, so the length of the interference signal in the time domain (that is, the pulse width T in the time domain) jam ) can be expressed as: T jam =Δ max -Δ min .

[0055] S1044: for each identified real target signal, according to the peak position, pulse width T p , sampling rate f s , the target signal bandwidth B and the number of short-time Fourier transform FFT points w are used to determine the time-frequency domain position of the real target signal.

[0056] Here, the time-frequency domain position of a real target signal is determined by the start position and end position of the time domain of the real target signal, and the start position and end position of the frequency domain of the real target signal. The specific determination method is an existing method and will not be repeated in the present invention.

[0057] For example, the starting position S of a real target signal in the time domain is t start and end position S t end Respectively expressed as:

[0058]

[0059] Wherein, Sig represents the peak position of the real target signal;

[0060] For example, the starting position of a real target signal in the frequency domain is and end position Respectively expressed as:

[0061]

[0062] wherein S l is the length of the real target signal in the frequency domain.

[0063] S1045、for each identified interference signal, determining the position of the time-frequency domain of the interference signal according to the peak position Jam of the interference signal, the pulse width T jam , the sampling rate f s , the target signal bandwidth B, the number of FFT points w, the minimum value Δ min , the maximum value Δ max , and the pulse width T p .

[0064] Here, the position of the time-frequency domain of an interference signal is determined by the start position and the end position of the time domain of the interference signal, and the start position and the end position of the frequency domain of the interference signal. For example, the start position and the end position of the time domain of an interference signal are respectively represented as:

[0065]

[0066] T jam = Δ max - Δ min .

[0067] wherein Jam represents the peak position of the interference signal, Δ offset represents the time domain offset of Jam relative to the center of the interference, and the offset is the time domain offset of Jam relative to the center of the interference when the interference signal exists frequency shift modulation, and the time domain offset is the difference between the pulse compression result center and the detected interference signal center.

[0068] For example, the start position and the end position of the frequency domain of an interference signal are respectively represented as:

[0069]

[0070] wherein f offset represents the offset of the interference signal in the frequency domain, and S l represents the length of the interference signal in the frequency domain.

[0071] For the above S106, the method of short-time Fourier transform is to segment and slide the window of the input signal s(t), then the segmented and windowed signal s(t)w(t-τ) can be regarded as a stationary signal, and the frequency component of the signal in each segment can be obtained using FFT. The signal obtained after the input signal is subjected to short-time Fourier transform can be represented as: where w(v) is a window function of the short-time Fourier transform, and Γ{·} represents the short-time Fourier operation. Figure 4 Fig. 1 is a schematic diagram of a time-frequency domain echo signal obtained after a short-time Fourier transform is performed on an original echo signal, i.e., a time-frequency diagram of the original echo signal. As shown in Fig. 1, it can be seen from the marked positions that, after the short-time Fourier transform, the real target signal and the interference signal in the echo signal can be separated in the time-frequency domain. Figure 4

[0072] In the present application, the interference suppression filter described in S107 is an H-shaped filter. Exemplarily, the expression of the filter is: H=~mask_s&mask_j; where H represents the interference suppression filter, mask_s represents the position of the real target signal in the time-frequency domain, mask_j represents the position of the interference signal in the time-frequency domain, "~" represents negation, and "&" represents AND operation. Exemplarily, Figure 5 Fig. 2 is a schematic diagram of the constructed interference suppression filter. Due to the non-periodic truncation of the STFT, the interference edge will produce a tailing phenomenon in the time-frequency domain, making it difficult to eliminate the residual energy of the interference. To solve this problem, the H-shaped filter designed in the present application can not only suppress the interference, but also cover the edge position of the interference. By covering the tailing produced by the edge position of the interference, the suppression ability of the residual interference edge can be improved, and the interference suppression ratio can be improved.

[0073] Exemplarily, Figure 6 Fig. (a) in Fig. 1 is the position of the interference signal in the time-frequency domain. As shown in Fig. (a) in Fig. 1, the edge of the interference signal is not covered. Figure 6 As shown in Fig. (a) in Fig. 1, the edge of the interference signal is not covered. Figure 6 Fig. (b) in Fig. 1 is a schematic diagram of covering the edge of the interference signal by using the interference suppression filter of the present application. Figure 7 Fig. 3 is a schematic diagram of a filtered time-frequency domain echo signal obtained after the time-frequency domain echo signal is filtered by using the interference suppression filter. Obviously, by suppressing the interference and covering the tailing produced by the edge position of the interference, the present application can improve the suppression ability of the interference and the residual interference edge, and improve the interference suppression ratio.

[0074] Exemplarily, Figure 8 Fig. (a) in Fig. 4 is a schematic diagram of the coherent accumulation result of the original echo signal without interference suppression, Figure 8 Fig. (b) in Fig. 4 is a schematic diagram of the coherent accumulation result of the signal obtained after the original echo signal is subjected to interference suppression by using the method of the present application. From Figure 8 It can be seen from Fig. 4 that the interference is suppressed to the noise level, and the real target signal is almost not lost, and the interference suppression effect is very good.

[0075] ​In the description of the specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described can be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples described in the specification.

[0076] In the specification, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude a plurality. Some measures are described in mutually different embodiments, but this does not mean that these measures cannot be combined to produce good results.

[0077] The above is a further detailed description of the present application in combination with specific preferred embodiments, and cannot be considered as limiting the specific implementation of the present application to these descriptions. For those skilled in the art, without departing from the concept of the present application, a number of simple deductions or substitutions can be made, which should be considered as belonging to the protection scope of the present application.

Claims

1. A method for slice interference localization and mitigation based on integral decomposition, characterized in that, The method comprises the following steps: receiving a raw echo signal and pulse compression on the raw echo signal to obtain a pulse-compressed echo signal; the raw echo signal contains a plurality of target signals, and the plurality of target signals contain real target signals and false target signals, wherein one false target signal is an interference signal; detecting the peak position of each target signal in the plurality of target signals from the pulse-compressed echo signal; for each target signal, performing integral decomposition on the raw echo signal based on the peak position of the target signal to obtain the integral decomposition result of the target signal; based on the integral decomposition results of the plurality of target signals, determining the time-frequency domain position of each real target signal and each interference signal; based on the time-frequency domain positions of all real target signals and all interference signals in the plurality of target signals, constructing an interference suppression filter; performing short-time Fourier transform on the raw echo signal to obtain a time-frequency domain echo signal; filtering the time-frequency domain echo signal by using the interference suppression filter to obtain a filtered time-frequency domain echo signal.

2. The integral resolution based slice interference localization and mitigation method of claim 1, wherein, The integral decomposition on the raw echo signal based on the peak position of the target signal to obtain the integral decomposition result of the target signal comprises: centered on the peak position of the target signal, a segment of length T p is selected from the original echo signal, and the selected segment is multiplied by the complex conjugate of the radar transmit signal to obtain an integrated decomposition result of the target signal, T p being the pulse width of the radar transmit signal.

3. The integral resolution based slice interference localization and mitigation method of claim 1, wherein, The determination of the time-frequency domain position of each real target signal and each interference signal based on the integral decomposition results of the plurality of target signals comprises: identifying real target signals and interference signals from the plurality of target signals according to the integral decomposition results of the plurality of target signals; the pulse width T of the radar transmitted signal p as the pulse width of each real target signal; For each identified interference signal, the pulse width T of the interference signal in the time domain is determined according to the integral decomposition result of the interference signal. jam ; Wherein, the pulse width T of the interference signal in the time domain jam is a minimum value Δ min With a maximum value Δ max The absolute value of the difference; For each real target signal identified, a position in time-frequency domain of the real target signal is determined according to a peak position of the real target signal, a pulse width T of the real target signal, a sampling rate f, a target signal bandwidth B and a number of short-time Fourier transform FFT points w. p s , the sampling rate f s , the target signal bandwidth B and the number of short-time Fourier transform FFT points w. For each identified interference signal, a position in time-frequency domain of the interference signal is determined according to the peak position of the interference signal, the pulse width T jam , the sampling rate f s , the target signal bandwidth B, the number of short-time Fourier transform FFT points w, the minimum value Δ min , the maximum value Δ max , and the pulse width T p .

4. The integral resolution based slice interference localization and mitigation method of claim 3, wherein, each integral decomposition result contains a plurality of amplitudes; The identification of real target signals and interference signals from the plurality of target signals according to the integral decomposition results of the plurality of target signals comprises: for each target signal, adding the plurality of amplitudes in the integral decomposition result of the target signal to obtain an amplitude variation curve of the target signal, wherein the amplitude variation curve is formed by a set of values obtained by the adding processing; performing linear fitting on the amplitude variation curve of the target signal to obtain a fitted amplitude variation curve of the target signal; calculating the similarity between the amplitude variation curve of the target signal and the fitted amplitude variation curve to obtain a similarity value; when the similarity value is greater than or equal to a preset threshold value, it indicates that the target signal is a real target signal; when the similarity value is less than the preset threshold value, it indicates that the target signal is an interference signal.

5. The integral resolution based slice interference localization and mitigation method of claim 4, wherein, determining the pulse width T of the interference signal in the time domain according to the integral decomposition result of the interference signal jam comprising: differencing the amplitude variation curve of the interference signal and the fitted amplitude variation curve of the interference signal to obtain a maximum difference point and a minimum difference point; the abscissa of the maximum difference point as the maximum value Δ max the abscissa of the minimum difference point as the minimum value Δ min ; calculating the minimum value Δ min the absolute value of the difference between the maximum value Δ max as the pulse width T jam of the interference signal in the time domain.

6. The integral resolution based slice interference locating and suppression method of claim 3, wherein, The time-frequency domain position of the real target signal is determined by the starting position and the ending position of the time domain of the real target signal, and the starting position and the ending position of the frequency domain of the real target signal; a start position of a time domain of the real target signal and an end position are respectively represented as: wherein Sig represents the peak position of the real target signal; a start position of a frequency domain of the real target signal and an end position are respectively expressed as: where S l is the length of the real target signal in the frequency domain.

7. The integral resolution based slice interference localization and suppression method of claim 3, wherein, The position of the time-frequency domain of the interference signal is determined by the start position and the end position of the time domain of the interference signal, and the start position and the end position of the frequency domain of the interference signal; the start position and the end position of the time domain of the interference signal are respectively represented as: and ​ T jam = Δ max - Δ min ; wherein Jam represents the peak position of the jamming signal, Δ offset represents the time-domain offset of Jam with respect to the jamming center; a start position of a frequency domain of the interference signal and an end position are respectively expressed as: wherein f offset represents the offset of the interference signal in the frequency domain, S l represents the length of the interference signal in the frequency domain.

8. The integral resolution based slice interference locating and suppression method of claim 1, wherein, The expression of the interference suppression filter is as follows: H = ~ mask_s & mask_j; Wherein, H represents the interference suppression filter, mask_s represents the position of the time-frequency domain of the real target signal, mask_j represents the position of the time-frequency domain of the interference signal, "~" represents negation, and "&" represents AND operation.

9. The integral resolution based slice interference locating and suppression method of claim 4, wherein, The principle expression of adding processing on the plurality of amplitudes in the integral decomposition result of the target signal is as follows: ID(k) = s r (p-T p / 2+k) · s ref (k), k = 1, 2,..., T p ; where p represents a peak position of the target signal, s r (p-T p / 2+k) represents a signal with a length of T p centered at p in the original echo signal, ID(k) represents a kth amplitude in an integral decomposition result of the target signal, M=T p , s ref (k) represents a complex conjugate of a radar transmitting signal, and P(m) represents a mth value in a set of values forming an amplitude variation curve of the target signal.

10. The integral resolution based slice interference localization and suppression method of claim 1, wherein, After the time-frequency domain echo signal is filtered by the interference suppression filter to obtain the filtered time-frequency domain echo signal, the method further comprises: Performing inverse short-time Fourier transform on the filtered time-frequency domain echo signal to obtain an interference-suppressed time domain echo signal.

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