A radar signal based polarization cancellation anti-jamming method and system

Abstract

The specification provides a radar signal based polarization cancellation anti-interference method and system, and relates to the technical field of radar signal processing. The method comprises determining a main polarization channel and an auxiliary channel of a subarray antenna, the main polarization channel and the auxiliary channel being orthogonal to each other; acquiring input signals of the main polarization channel and the auxiliary channel; determining an interference signal weight coefficient of the auxiliary channel by calculating noise variance of the first matrix; and polarizing and canceling interference signals of the second matrix according to the first matrix and the interference signal weight coefficient of the auxiliary channel. The method can cancel interference signals in the main polarization channel to obtain low-interference or no-interference output signals, thereby improving the signal-to-noise ratio of the radar system and facilitating subsequent radar signal processing detection. Moreover, the polarization cancellation interference method is suitable for radar systems under a dual-polarization array antenna, and has the advantage of strong applicability.

Description

Technical Field

[0001] This specification relates to the field of radar signal processing technology, and more specifically, to a polarization cancellation anti-interference method and system based on radar signals. Background Technology

[0002] With the continuous development of radar technology, the interference environment faced by radar is becoming increasingly complex. Traditional anti-jamming methods, such as time-domain and frequency-domain methods, can no longer meet the needs of radar systems. In particular, in some situations, traditional time-domain and frequency-domain anti-jamming methods cannot meet the requirements of radar systems, such as when the main lobe interference is much stronger than the target echo and the auxiliary antenna and the main antenna are in an orthogonal state. This is an example where traditional time-domain and frequency-domain anti-jamming methods are not applicable to the application scenario of dual-polarized radar array antennas. Summary of the Invention

[0003] The purpose of this specification is to provide a polarization cancellation anti-interference method based on radar signals, which can solve the problem of poor anti-interference performance of traditional methods under dual-polarization radar array antennas.

[0004] The embodiments described in this specification are implemented as follows:

[0005] On the one hand, this specification provides a polarization cancellation anti-interference method based on radar signals, which mainly includes:

[0006] Determine the main polarization channel and the auxiliary channel of the subarray antenna, wherein the main polarization channel and the auxiliary channel are orthogonal to each other;

[0007] Based on the obtained input signal of the main polarization channel and the input signal of the auxiliary channel, a first matrix and a second matrix are determined. The first matrix can characterize the autocorrelation of the input signal of the auxiliary channel, and the second matrix can characterize the cross-correlation between the input signal of the auxiliary channel and the input signal of the main polarization channel.

[0008] The interference signal weighting coefficient of the auxiliary channel is determined by calculating the noise variance of the first matrix.

[0009] Using the interference signal weighting coefficients of the auxiliary channel, the interference signal of the second matrix is ​​polarized and canceled according to the first matrix.

[0010] On the other hand, this specification provides a polarization cancellation anti-jamming system based on radar signals, mainly including:

[0011] The channel determination module is used to determine the main polarization channel and the auxiliary channel of the subarray antenna, wherein the main polarization channel and the auxiliary channel are orthogonal to each other.

[0012] The calculation module is used to determine a first matrix and a second matrix based on the obtained input signal of the main polarization channel and the input signal of the auxiliary channel. The first matrix can characterize the autocorrelation of the input signal of the auxiliary channel, and the second matrix can characterize the cross-correlation between the input signal of the auxiliary channel and the input signal of the main polarization channel.

[0013] The weighting coefficient determination module is used to determine the interference signal weighting coefficient of the auxiliary channel by calculating the noise variance of the first matrix.

[0014] The cancellation module is used to polarize and cancel the interference signal of the second matrix according to the first matrix, using the interference signal weighting coefficient of the auxiliary channel.

[0015] The embodiments described in this specification have at least the following advantages or beneficial effects:

[0016] This polarization cancellation anti-interference method calculates the weighting coefficients of the auxiliary channel based on the input signals of the main polarization channel and the auxiliary channel, thereby canceling interference signals in the main polarization channel to obtain a low-interference or interference-free output signal. This improves the signal-to-noise ratio of the radar system, facilitates subsequent radar signal processing, and ultimately achieves accurate tracking and identification of real target signals. Furthermore, this polarization cancellation method is applicable to radar systems with dual-polarization array antennas, demonstrating strong applicability. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this specification, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this specification and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the polarization cancellation anti-interference method based on radar signals provided in this specification.

[0019] Figure 2 This is a schematic diagram of the polarization cancellation process for the k-th main polarization channel provided in this specification.

[0020] Figure 3 A schematic diagram of the pulse compression process for the polarization radar signal provided in this specification;

[0021] Figure 4 This is a schematic diagram of the radar signal polarization cancellation anti-interference system provided in this specification. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments in this specification clearer, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Generally, the components of the embodiments of this specification described and shown in the accompanying drawings can be arranged and designed in various different configurations.

[0023] Please refer to Figures 1 to 3 One embodiment of this specification provides a polarization cancellation anti-interference method based on radar signals, mainly including:

[0024] Step 102: Determine the main polarization channel and the auxiliary channel of the subarray antenna, wherein the main polarization channel and the auxiliary channel are orthogonal to each other;

[0025] Step 104: Based on the obtained input signal of the main polarization channel and the input signal of the auxiliary channel, determine a first matrix and a second matrix. The first matrix can characterize the autocorrelation of the input signal of the auxiliary channel, and the second matrix can characterize the cross-correlation between the input signal of the auxiliary channel and the input signal of the main polarization channel.

[0026] Step 106: Determine the interference signal weighting coefficient of the auxiliary channel by calculating the noise variance of the first matrix;

[0027] Step 108: Using the interference signal weighting coefficient of the auxiliary channel, polarize and cancel the interference signal of the second matrix according to the first matrix.

[0028] In this embodiment, the above method is specifically applied to the condition that the main lobe interference is much stronger than the target echo and the main antenna and the auxiliary antenna are orthogonal. Under the condition that the main lobe interference is much stronger than the target echo, the energy received by the auxiliary antenna is mainly interference energy. At this time, from the perspective of polarization, the antenna structure and the side lobe cancellation structure are consistent.

[0029] In this embodiment, the main polarization channel is the receiving channel of the main antenna, the auxiliary channel is the receiving channel of the auxiliary antenna, and the signal received by the receiving channel is the input signal.

[0030] Specifically, the aforementioned polarization-based interference cancellation method calculates the weighting coefficients of the auxiliary channel based on the input signals of the main polarization channel and the auxiliary channel, thereby canceling interference signals in the main polarization channel to obtain low-interference or interference-free output signals. This improves the signal-to-noise ratio of the radar system, facilitates subsequent radar signal processing, and ultimately achieves accurate tracking and identification of real target signals. Furthermore, the aforementioned polarization-based interference cancellation method is applicable to radar systems with dual-polarization array antennas, offering the advantage of strong applicability.

[0031] In this embodiment, one specific implementation of step 102 is as follows:

[0032] Step 112: When the main polarization channel is determined to be horizontally polarized, the auxiliary channel is vertically polarized;

[0033] Step 114: When the main polarization channel is determined to be vertically polarized, the auxiliary channel is horizontally polarized.

[0034] In this embodiment, under the condition that the main lobe interference is much stronger than the target echo, if the main polarization channel is horizontally polarized, then the vertically polarized subarray is selected as the auxiliary subarray, that is, the above-mentioned auxiliary channel is vertically polarized; if the main polarization channel is vertically polarized, then the horizontally polarized auxiliary channel is selected.

[0035] In this embodiment, by means of the above-described configuration, the space spanned by the echo signal vectors in the auxiliary subarray is the interference space. Each main polarization channel is projected onto the interference space, and the interference of the main polarization channel is eliminated by removing the projection from each of the main polarization channels, thereby achieving the effect of suppressing the interference signal.

[0036] In this embodiment, one specific implementation of step 104 is as follows:

[0037] Based on the input signal of the auxiliary channel, the first matrix RxX is determined as follows:

[0038] R XX =A T A

[0039] Where A is the matrix composed of all auxiliary channels, namely {A1, A2, ..., A...} i}, A i A is the input signal of the i-th auxiliary channel. T Let A be the conjugate transpose of A.

[0040] Specifically, the number of sampling points for the input signal of the i-th auxiliary channel is 1440, that is, the aforementioned A i Given a 1440×1 matrix, the above {A1, A2, ..., A... i The matrix A is a 1440×i matrix, which is the matrix A composed of the above auxiliary channels. T It is an i×1440 matrix.

[0041] In this embodiment, the aforementioned first matrix R XX It can characterize the autocorrelation properties of the input signal of the auxiliary channel. And the aforementioned first matrix R... XX It is a positive semi-definite matrix.

[0042] In this embodiment, one specific implementation of step 104 is as follows:

[0043] Step 132: Determine the second matrix rxy based on the matrix composed of each auxiliary channel and each main polarization channel. k That is:

[0044] rxy k =A T B k

[0045] Among them, B k This is the input signal for the k-th main polarization channel.

[0046] In this embodiment, the input signal of the k-th main polarization channel is a 1440×1 matrix, where 1440 is the number of sampling points of the main polarization channel.

[0047] In other embodiments, the number of signal sampling points for the main polarization channel and the auxiliary channel can be set to other values ​​according to the actual application, and the number of sampling points for the main polarization channel and the auxiliary channel should be consistent.

[0048] In this embodiment, the aforementioned second matrix rxy k It can characterize the cross-correlation between the input signal of the auxiliary channel and the input signal of the k-th main polarization channel.

[0049] In this embodiment, before step 104, the following steps are also included:

[0050] Step 142: Obtain the original signal of the main polarization channel and the original signal of the auxiliary channel;

[0051] Step 144: Collect the original signals of the main polarization channel and the auxiliary channel respectively according to the preset data acquisition rate;

[0052] Step 146: Perform down-conversion processing on the acquired signals to obtain the input signal of the main polarization channel and the input signal of the auxiliary channel.

[0053] In this embodiment, the down-converted signal of the original signal is used as the input signal of the main polarization channel and the input signal of the auxiliary channel.

[0054] In this embodiment, one specific implementation of step 106 is as follows:

[0055] Step 152: Determine the noise variance of each auxiliary channel based on the average value of the input signal of each auxiliary channel and the number of signal sampling points of each auxiliary channel;

[0056] Step 154: Determine the noise variance of the first matrix based on the noise variance of each auxiliary channel;

[0057] Step 156: Determine the interference signal weighting coefficient of the auxiliary channel based on the noise variance of the first matrix, the first matrix, and the second matrix.

[0058] In this embodiment, the noise variance has a significant impact on the interference signal weighting coefficient of the auxiliary channel. The larger the noise variance value, the greater the fluctuation of the input signal of the auxiliary channel.

[0059] In this embodiment, by setting the noise variance, the quality and accuracy of the above signal can be effectively improved.

[0060] In this embodiment, one specific implementation of step 152 is as follows:

[0061] Step 162, with A ij Let be the number of the j-th sampling points of the input signal of the i-th auxiliary channel, then the average value μ of the input signal of the i-th auxiliary channel is... i for:

[0062] μ i =(A i1 +A i2 +…+A ij ) / j

[0063] Step 164: Noise variance of the i-th auxiliary channel for:

[0064]

[0065] In this embodiment, one specific implementation of step 156 is as follows:

[0066] Step 172: Let σ be the noise variance of the first matrix. 2 That is:

[0067]

[0068] Step 174, the interference signal weighting coefficient ω of the auxiliary channel k for:

[0069] ω k =(Rxx+σ) 2 ·I) -1 rxy k

[0070] Where I is the identity matrix, and the dimension of the identity matrix is ​​the number of auxiliary channels. σ 2• I represents the product of the noise variance and the corresponding element of the identity matrix I.

[0071] In this embodiment, one specific implementation of step 108 is as follows:

[0072] Step 182: The polarization cancellation output signal C corresponding to the k-th main polarization channel. k for:

[0073] C k =B k -Aω k .

[0074] In this embodiment, the interference signal of the main polarization channel is eliminated by the above-described specific method, that is, the projection of the main polarization channel onto the interference space is removed, so as to suppress the interference signal.

[0075] Please refer to Figure 4 Another embodiment of this specification provides a polarization cancellation anti-jamming system based on radar signals, mainly comprising:

[0076] The channel determination module 202 is used to determine the main polarization channel and the auxiliary channel of the subarray antenna, wherein the main polarization channel and the auxiliary channel are orthogonal to each other.

[0077] The calculation module 204 is used to determine a first matrix and a second matrix based on the obtained input signal of the main polarization channel and the input signal of the auxiliary channel. The first matrix can characterize the autocorrelation of the input signal of the auxiliary channel, and the second matrix can characterize the cross-correlation between the input signal of the auxiliary channel and the input signal of the main polarization channel.

[0078] The weighting coefficient determination module 206 is used to determine the interference signal weighting coefficient of the auxiliary channel by calculating the noise variance of the first matrix.

[0079] The cancellation module 208 is used to polarize and cancel the interference signal of the second matrix according to the first matrix, using the interference signal weighting coefficient of the auxiliary channel.

[0080] This polarization cancellation anti-interference system calculates the weighting coefficients of the auxiliary channels based on the input signals of the main polarization channel and the auxiliary channels. This cancels interference signals in the main polarization channel, resulting in a low-interference or interference-free output signal. This improves the signal-to-noise ratio of the radar system, facilitating subsequent radar signal processing and ultimately enabling accurate tracking and identification of real target signals. Furthermore, this polarization cancellation method is applicable to radar systems with dual-polarization array antennas, offering strong applicability.

[0081] In this embodiment, the channel determination module 202 is used to determine that when the main polarization channel is horizontally polarized, the auxiliary channel is vertically polarized; and when the main polarization channel is vertically polarized, the auxiliary channel is horizontally polarized. Through this configuration, the space spanned by the echo signal vectors in the auxiliary subarray becomes the interference space. By projecting each main polarization channel onto the interference space and removing the projection from each main polarization channel, the interference of the main polarization channel is canceled, thereby suppressing the interference signal.

[0082] In this embodiment, the calculation module 204 is used to determine the first matrix Rxx based on the input signal of the auxiliary channel, that is: Rxx = A T A, where A is the matrix composed of all auxiliary channels, i.e., {A1, A2, ..., A...} i The transpose of}, A i A is the input signal of the i-th auxiliary channel. T Let r be the conjugate transpose of A. Based on the matrices formed by the auxiliary channels and the main polarization channels, determine the second matrix rxy. k That is: rxy k =A T B k Among them, B k Let Rx be the input signal of the k-th main polarization channel. The first matrix Rxx characterizes the autocorrelation properties of the input signal of the auxiliary channel. Furthermore, the first matrix Rxx is a positive semi-definite matrix. The second matrix rxy... k It can characterize the cross-correlation between the input signal of the auxiliary channel and the input signal of the k-th main polarization channel.

[0083] In this embodiment, the system further includes an acquisition module 210, used to acquire the original signal of the main polarization channel and the original signal of the auxiliary channel; to acquire the original signal of the main polarization channel and the original signal of the auxiliary channel respectively according to a preset data acquisition rate; and to perform down-conversion processing on the acquired signals to obtain the input signal of the main polarization channel and the input signal of the auxiliary channel respectively.

[0084] In this embodiment, the weighting coefficient determination module 206 is used to determine the noise variance of each auxiliary channel based on the average value of the input signal of each auxiliary channel and the number of signal sampling points of each auxiliary channel; to determine the noise variance of the first matrix based on the noise variance of each auxiliary channel; and to determine the interference signal weighting coefficient of the auxiliary channel based on the noise variance of the first matrix, the first matrix, and the second matrix. (Using A...) ij Let be the number of the j-th sampling points of the input signal of the i-th auxiliary channel, then the average value μ of the input signal of the i-th auxiliary channel is... iFor: μ i =(A i1 +A i2 +…+A ij ) / j, the noise variance of the i-th auxiliary channel. for: Let σ be the noise variance of the first matrix. 2 That is: The interference signal weighting coefficient ω of the auxiliary channel k For: ω k =(Rxx+σ) 2 ·I) - 1 rxy k , where I is the identity matrix, and the dimension of the identity matrix is ​​the number of auxiliary channels. σ 2 • I represents the product of the noise variance and the corresponding element of the identity matrix I. The noise variance significantly affects the interference signal weighting coefficient of the auxiliary channel; a larger noise variance value results in greater fluctuations in the input signal of the auxiliary channel. By setting the noise variance, the quality and accuracy of the signal can be effectively improved.

[0085] In this embodiment, the cancellation module 208 is used for the polarization cancellation output signal C corresponding to the k-th main polarization channel. k For: C k =B k -Aω k The specific methods described above are used to eliminate interference signals from the main polarization channel, which means removing the projection of the main polarization channel into the interference space, thereby suppressing interference signals.

[0086] Based on the same inventive concept, another embodiment of this specification provides a computer-readable storage medium storing one or more programs, which, when executed by an electronic device including multiple application programs, cause the electronic device to perform... Figure 1 The corresponding embodiment provides a polarization cancellation anti-interference method based on radar signals.

[0087] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0088] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0089] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 The device that provides the function specified in each box.

[0091] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0093] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0094] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0095] The above description is merely an embodiment of this application and is not intended to limit this specification. Various modifications and variations can be made to this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims.

Claims

1. A radar signal based polarization cancellation anti-jamming method, characterized in that, include: Determine the main polarization channel and the auxiliary channel of the subarray antenna, wherein the main polarization channel and the auxiliary channel are orthogonal to each other; Based on the acquired input signals of the main polarization channel and the auxiliary channel, a first matrix and a second matrix are determined. The first matrix characterizes the autocorrelation of the input signal of the auxiliary channel, and the second matrix characterizes the cross-correlation between the input signal of the auxiliary channel and the input signal of the main polarization channel, including: Based on the input signal of the auxiliary channel, determine the first matrix. That is: in, The matrix composed of all auxiliary channels is, in other words, , For the first The input signal of the auxiliary channel described above, for The conjugate transpose of ; The second matrix is ​​determined based on the matrix formed by the auxiliary channels and the main polarization channels. That is: in, For the first The input signal of the main polarization channel described in the circuit; The interference signal weighting coefficients of the auxiliary channel are determined by calculating the noise variance of the first matrix, including: Based on the average value of the input signal of each auxiliary channel and the number of signal sampling points of each auxiliary channel, the noise variance of each auxiliary channel is determined, including: by Let be the number of the j-th sampling points of the input signal of the i-th auxiliary channel, then the j-th sampling point is... The average value of the input signal of the auxiliary channel mentioned above for: The noise variance of the i-th auxiliary channel for: The noise variance of the first matrix is ​​determined based on the noise variance of each of the auxiliary channels. Based on the noise variance of the first matrix, the first matrix, and the second matrix, the interference signal weighting coefficients of the auxiliary channel are determined, including: The noise variance of the first matrix is That is: The interference signal weighting coefficient of the auxiliary channel for: in, The identity matrix is ​​defined as the number of auxiliary channels. Represents the noise variance and the identity matrix Multiply corresponding elements; Using the interference signal weighting coefficients of the auxiliary channel, and based on the first matrix, polarization cancellation of the interference signal in the second matrix includes: No. The polarization cancellation output signal corresponding to the main polarization channel described above. for: 。 2. The polarization cancellation anti-interference method based on radar signals according to claim 1, characterized in that, The determination of the main polarization channel and auxiliary channel of the subarray antenna includes: When the main polarization channel is determined to be horizontally polarized, the auxiliary channel is vertically polarized; When the main polarization channel is determined to be vertically polarized, the auxiliary channel is horizontally polarized.

3. The polarization cancellation anti-interference method based on radar signals according to claim 1, characterized in that, Before determining the first matrix and the second matrix based on the acquired input signals of the main polarization channel and the auxiliary channel, the process includes: Obtain the original signal of the main polarization channel and the original signal of the auxiliary channel; According to the preset data acquisition rate, the original signals of the main polarization channel and the original signals of the auxiliary channel are acquired respectively. The acquired signals are down-converted to obtain the input signals of the main polarization channel and the auxiliary channel, respectively.

4. A polarization cancellation anti-jamming system based on radar signals, executing the polarization cancellation anti-jamming method based on radar signals as described in claim 1, characterized in that, include: The channel determination module is used to determine the main polarization channel and the auxiliary channel of the subarray antenna, wherein the main polarization channel and the auxiliary channel are orthogonal to each other. The calculation module is used to determine a first matrix and a second matrix based on the obtained input signal of the main polarization channel and the input signal of the auxiliary channel. The first matrix can characterize the autocorrelation of the input signal of the auxiliary channel, and the second matrix can characterize the cross-correlation between the input signal of the auxiliary channel and the input signal of the main polarization channel. The weighting coefficient determination module is used to determine the interference signal weighting coefficient of the auxiliary channel by calculating the noise variance of the first matrix. The cancellation module is used to polarize and cancel the interference signal of the second matrix according to the first matrix, using the interference signal weighting coefficient of the auxiliary channel.

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