Highly robust floating high-frequency ground wave radar point target arrival angle estimation method and device

Abstract

The present invention discloses a highly robust method for estimating the angle of arrival of a point target of a floating high-frequency ground wave radar. By performing yaw compensation through adaptive beamforming, the accuracy of the point target angle of arrival estimation can be effectively improved. However, with the existence of different formations and antenna pattern distortion, the point target angle of arrival estimation after yaw compensation still has deviations and the compensation will cause a loss of signal-to-noise ratio, making it difficult to ensure robustness. By reducing the angle constraint range of the adaptive beamforming, the accuracy of the angle of arrival estimation after yaw compensation can be further improved. And by iteratively reducing the angle constraint range step by step, the accuracy of the angle of arrival estimation is continuously improved. In addition, constraining the quadratic modulus of the adaptive weight vector can effectively avoid the loss of signal-to-noise ratio during the yaw compensation process. The present invention is a method with high robustness and good versatility, which is suitable for the angle of arrival estimation of point targets of floating high-frequency ground wave radar and has promotion and application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar array signal processing, and more specifically, relates to a method and device for estimating the angle of arrival of a point target of a highly robust floating high-frequency ground wave radar. Background Art

[0002] Due to its beyond-horizon detection capabilities, high-frequency ground-wave radar (HFSGWR) enables all-weather, high-precision monitoring of exclusive economic zones (EEZs) within 200 nautical miles. To further expand its application and extend its reach into the deep blue, the development of floating HFSGWR is essential. Floating HFSGWR is unconstrained by coastlines, extending its detection range and conserving precious coastal land resources for tourism and aquaculture. Floating HFSGWR can also serve as dynamic nodes in HFSGWR networks, further enhancing the detection capabilities of existing HFSGWR networks. However, within the relatively long coherent integration timeframe of several minutes, the yaw rotation of floating HFSGWR reduces the accuracy of point target arrival angle estimates.

[0003] K.W.Gurgel (1989), Tian Yingwei (2013), and Xie Junhao (2016) all controlled floating platforms to advance at a constant speed to avoid yaw rotation. Wu Xiongbin (2016) attempted to anchor a floating platform at sea, where uncontrollable yaw rotation became a key factor limiting the accuracy of angle-of-arrival estimation. To compensate for yaw, the research team used adaptive beamforming combined with the measured yaw angle, ensuring that the real-time beam and the reference beam remained consistent during yaw rotation. This method can effectively compensate for yaw rotation and improve the accuracy of angle-of-arrival estimation. However, due to different formations and antenna pattern distortion, the arrival angle estimation of point targets still has deviations after yaw compensation, which can lead to a decrease in the signal-to-noise ratio of the compensated signal, making robustness difficult to ensure. Summary of the Invention

[0004] The present invention addresses the problem of difficulty in ensuring the robustness of arrival angle estimation when adaptive beamforming is used to perform yaw compensation for a floating high-frequency ground wave radar in different formations and with antenna pattern distortion. First, the angular focus length and angular focus center are determined to determine the angular constraint range of the adaptive beamforming. Second, the balance between the noise power gain and the beam holding factor under the angular constraint range is considered to obtain an adaptive weight vector with balanced focus. Then, the noise power gain is constrained to be lower than 0 dB to obtain an adaptive weight vector with no signal-to-noise ratio loss and a smaller angular constraint range. Finally, the adaptive weight vector is used to perform yaw compensation through beamforming, and the arrival angle estimation result after yaw compensation is obtained through the MUSIC (Multiple Signal Classification) algorithm in the beam space. The estimated arrival angle is used as the new angular focus center and the angular focus length is reduced, and a highly robust point target arrival angle estimation result is obtained through step-by-step iteration.

[0005] To achieve the above object, according to one aspect of the present invention, a highly robust floating high-frequency ground wave radar point target arrival angle estimation method is provided, comprising the following steps:

[0006] (1) Determine the angular focus length θ during the iteration process l and the angle focusing center θ c , in the first iteration, the angular focus length is 360 ° The angular focus center is the arrival angle estimation result obtained by using conventional beamforming; when this step is repeated again, the angular focus length is The angular focus center is taken as the angular focus length The arrival angle estimation result after compensation is , and T is the number of iterations;

[0007]

[0008] in,

[0009]

[0010]

[0011]

[0012] k represents the kth beam channel, K is the number of beam channels, K is also the number of antenna channels, k=1,2,…,K,w 0k is the reference weight vector, is the real-time yaw angle, is the reference yaw angle within a coherent integration time, ξ is the balance factor describing the contribution weight of noise power gain and beam keeping factor, θ is the azimuth angle, is the reference beam, is the real-time array steering vector, is the reference array steering vector, and as follows

[0013]

[0014]

[0015] in,

[0016]

[0017]

[0018]

[0019]

[0020] k0 is the working electromagnetic wave number, is the unit steering vector in the direction of θ, A r0 is the coordinate matrix of the receiving antenna array, a r0k is the three-dimensional coordinate vector of antenna k, x r0k is the X-axis coordinate, y r0k is the Y-axis coordinate, z r0k is the Z-axis coordinate, is the rotation matrix describing the real-time yaw rotation, is the rotation matrix describing the reference yaw rotation;

[0021] (3) Calculate the noise power gain and beam holding factor values corresponding to different balancing factors. The noise power gain calculation method is as follows:

[0022]

[0023] The beam holding factor is calculated as follows:

[0024]

[0025] in,

[0026]

[0027] For adaptive beamforming, in order to avoid signal-to-noise ratio loss, a balance factor value range is selected that makes the noise power gain less than 0dB; then a balance factor ξ is determined that minimizes the beam holding factor within this value range. D , the adaptive weight vector at this time is a highly robust adaptive weight vector;

[0028] (4) The resulting highly robust adaptive weight vector is used to beamform the sampled data of the antenna channel to obtain compensated data for the beam channel. The arrival angle of the floating high-frequency ground wave radar point target is then estimated using the beamspace MUSIC algorithm. This yaw-compensated point target arrival angle is used as the new angular focus center, and the angular focus length is further reduced. The entire process is repeated to obtain a more robust point target arrival angle estimation result.

[0029] In one embodiment of the present invention, step (4) specifically includes:

[0030] A total of K reference beams are determined as follows:

[0031]

[0032] Calculate the corresponding highly robust adaptive weight vector for each reference beam Beamforming is performed using an adaptive weight vector to obtain beam channel compensation data. The yaw compensation operation is repeated for each frequency sweep cycle. The arrival angle is then estimated using the beam channel-based MUSIC angle search method on the beam channel compensation data as follows:

[0033]

[0034] U BN It is composed of K×M eigenvectors corresponding to the noise subspace of the beam channel compensation data n Matrix, M n is the dimension of the noise subspace, 1≤M n ≤K-1; search P MUSIC The peak value of (θ) can be used to obtain the arrival angle estimation result of the yaw-compensated signal. Repeat all steps, and the arrival angle estimation result outputted after the T-th repetition is the final arrival angle estimation result.

[0035] According to another aspect of the present invention, a highly robust floating high-frequency ground wave radar point target angle of arrival estimation device is provided. The device includes at least one processor and a memory, wherein the at least one processor and the memory are connected via a data bus. The memory stores instructions executable by the at least one processor. After being executed by the processor, the instructions are used to complete the highly robust floating high-frequency ground wave radar point target angle of arrival estimation method.

[0036] In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:

[0037] (1) When the balancing factor is zero and the angle constraint range is 360°, the present invention is the background technology for constraining only the beam holding factor. The present invention is a more versatile solution.

[0038] (2) The present invention can avoid the signal-to-noise ratio loss caused by only constraining the beam holding factor, and is more suitable for the arrival angle estimation of weak target echoes of floating high-frequency ground wave radar;

[0039] (3) The smaller angle constraint range enables adaptive beamforming to have stronger control over the beam, which can improve the robustness of arrival angle estimation for point targets such as aircraft and ships. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a flow chart of the method for estimating the angle of arrival of a point target using a high-robustness floating high-frequency ground wave radar in the present invention. DETAILED DESCRIPTION

[0041] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0042] The purpose of the present invention is to provide a highly robust adaptive beamforming scheme that is applicable to yaw compensation of a floating high-frequency ground wave radar. The technical problems to be solved include: (1) determination of the angular focus length and the angular focus center during the iterative process of highly robust adaptive beamforming; (2) calculation of the adaptive weight vector for balanced focusing; (3) determination of the balancing factor corresponding to the adaptive weight vector with no signal-to-noise ratio loss and a smaller angular constraint range; and (4) estimation of the arrival angle in the beam space.

[0043] In order to solve the above technical problems, the present invention provides a highly robust floating high-frequency ground wave radar point target arrival angle estimation method, comprising the following steps:

[0044] (1) Determine the angular focus length θ during the iteration process l and the angle focusing center θ c In the first iteration, the angular focus length is 360°, and the angular focus center is the arrival angle estimation result obtained by using conventional beamforming; when repeating this step again, the angular focus length is The angular focus center is taken as the angular focus length The arrival angle estimation result after compensation is , and T is the number of iterations;

[0045] (2) According to the determined angular focus length and angular focus center, the adaptive weight vector of balanced focus is obtained as follows:

[0046]

[0047] in,

[0048]

[0049]

[0050]

[0051] k represents the kth beam channel, K is the number of beam channels, K is also the number of antenna channels, k=1,2,…,K,w 0k is the reference weight vector, is the real-time yaw angle, is the reference yaw angle within a coherent integration time, ξ is the balance factor describing the contribution weight of noise power gain and beam keeping factor, θ is the azimuth angle, is the reference beam, is the real-time array steering vector, is the reference array steering vector, and as follows

[0052]

[0053]

[0054] in,

[0055]

[0056]

[0057]

[0058]

[0059] k0 is the working electromagnetic wave number, is the unit steering vector in the direction of θ, A r0 is the coordinate matrix of the receiving antenna array, a r0k is the three-dimensional coordinate vector of antenna k, x r0k is the X-axis coordinate, y r0k is the Y-axis coordinate, z r0k is the Z-axis coordinate, is the rotation matrix describing the real-time yaw rotation, is the rotation matrix describing the reference yaw rotation;

[0060] (3) Calculate the noise power gain and beam holding factor values corresponding to different balancing factors. The noise power gain calculation method is as follows:

[0061]

[0062] The beam holding factor is calculated as follows:

[0063]

[0064] in,

[0065]

[0066] For adaptive beamforming, in order to avoid signal-to-noise ratio loss, a balance factor value range is selected that makes the noise power gain less than 0dB; then a balance factor ξ is determined that minimizes the beam holding factor within this value range. D , the adaptive weight vector at this time This is the highly robust adaptive weight vector of the present invention;

[0067] (4) The resulting highly robust adaptive weight vector is used to beamform the sampled data of the antenna channel to obtain compensated data for the beam channel. The arrival angle of the floating high-frequency ground wave radar point target is then estimated using the beamspace MUSIC algorithm. This yaw-compensated point target arrival angle is used as the new angular focus center, and the angular focus length is further reduced. The entire process is repeated to obtain a more robust point target arrival angle estimation result.

[0068] Specifically, the arrival angle of the floating high-frequency ground wave radar point target is estimated by the beam space MUSIC algorithm. Specifically, a total of K reference beams are determined as follows:

[0069]

[0070] Calculate the corresponding highly robust adaptive weight vector for each reference beam Beamforming is performed using an adaptive weight vector to obtain beam channel compensation data. The yaw compensation operation is repeated for each frequency sweep cycle. The arrival angle is then estimated using the beam channel-based MUSIC angle search method on the beam channel compensation data as follows:

[0071]

[0072] U BN It is composed of K×M eigenvectors corresponding to the noise subspace of the beam channel compensation data n Matrix, M n is the dimension of the noise subspace, 1≤M n ≤K-1; search P MUSIC The peak value of (θ) can be used to obtain the arrival angle estimation result of the yaw-compensated signal. Repeat all steps, and the arrival angle estimation result outputted after the T-th repetition is the final arrival angle estimation result.

[0073] Furthermore, the present invention also provides a highly robust floating high-frequency ground wave radar point target arrival angle estimation device, comprising at least one processor and a memory, wherein the at least one processor and the memory are connected via a data bus, and the memory stores instructions that can be executed by the at least one processor. After being executed by the processor, the instructions are used to complete the highly robust floating high-frequency ground wave radar point target arrival angle estimation method.

[0074] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A highly robust floating high-frequency ground wave radar point target arrival angle estimation method, characterized in that: The steps include: (1) Determine the angular focus length during the iteration process and angle focus center , in the first iteration, the angular focus length is The angular focus center is the arrival angle estimation result obtained by using conventional beamforming; when this step is repeated again, the angular focus length is , the angle focusing center takes the angle focusing length as The arrival angle estimation result after compensation is , and T is the number of iterations; (2) According to the determined angular focusing length and angular focusing center, the adaptive weight vector of balanced focusing is obtained as (1) in, (2) (3) (4) Indicates the beam channels, is the number of beam channels, is also the number of antenna channels, is the reference weight vector, is the real-time yaw angle, is the reference yaw angle within a coherent integration time, is a balancing factor describing the contribution weight of noise power gain and beam-keeping factor, is the azimuth, is the reference beam, , and as follows (5) (6) in, (7) (8) (9) (10) is the working electromagnetic wave number, yes The unit steering vector of the direction, is the coordinate matrix of the receiving antenna array, for The three-dimensional coordinate vector of antenna No. is the X-axis coordinate, is the Y-axis coordinate, is the Z-axis coordinate, is the rotation matrix describing the real-time yaw rotation, is the rotation matrix describing the reference yaw rotation; (3) Calculate the noise power gain and beam holding factor values corresponding to different balancing factors. The noise power gain calculation method is as follows: (11) The beam holding factor is calculated as follows: (12) in, (13) For adaptive beamforming, in order to avoid signal-to-noise ratio loss, a balance factor value range is selected that makes the noise power gain less than 0 dB; then the balance factor that makes the beam holding factor take the minimum value within this value range is determined. , the adaptive weight vector at this time is a highly robust adaptive weight vector; (4) The obtained highly robust adaptive weight vector is used to perform beamforming on the sampling data of the antenna channel to obtain the compensation data of the beam channel. Then, the arrival angle of the floating high-frequency ground wave radar point target is estimated by the MUSIC algorithm in the beam space. The arrival angle of the point target after yaw compensation is used as the new angle focusing center, and the angle focusing length is further reduced. The whole process is repeated to obtain a more robust point target arrival angle estimation result.

2. The method for estimating the angle of arrival of a point target using a high-robustness floating high-frequency ground wave radar according to claim 1, wherein: The step (4) specifically includes: A total of K reference beams are determined as follows: (14) Calculate the corresponding highly robust adaptive weight vector for each reference beam , use adaptive weight vector to perform beamforming to obtain beam channel compensation data, and repeat the yaw compensation operation for each frequency sweep cycle; then use the beam channel-based MUSIC angle search method to estimate the arrival angle of the beam channel compensation data, as follows: (15) It is composed of the eigenvectors corresponding to the noise subspace of the beam channel compensation data matrix, is the dimension of the noise subspace, ;search The arrival angle estimation result of the yaw-compensated signal can be obtained by calculating the peak value of the yaw-compensated signal. Repeat all steps, and the arrival angle estimation result outputted after the T-th repetition is the final arrival angle estimation result.

3. A highly robust floating high-frequency ground wave radar point target arrival angle estimation device, characterized by: The method comprises at least one processor and a memory, wherein the at least one processor and the memory are connected via a data bus, and the memory stores instructions executable by the at least one processor, wherein the instructions, after being executed by the processor, are used to complete the method for estimating the angle of arrival of a point target using a highly robust floating high-frequency ground wave radar according to any one of claims 1 to 2.

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