An improved generalized monopulse direction finding method based on first-order newton iteration

Abstract

The application relates to the technical field of radar signal processing, and discloses an improved generalized monopulse angle measurement method based on first-order Newton iteration, which adopts ADBF technology to calculate multi-beam ADBF weight values and echoes, carries out target detection on sum beam echoes to obtain the positions of targets, and extracts all beam target echoes; a multi-beam angle measurement model based on sum beams, azimuth difference beams and pitch difference beams is established, a first-order Newton iteration method is used to iteratively calculate target angles, until the iteration result converges, so that the target angle is obtained. The application establishes a multi-beam ADBF angle measurement model, uses the first-order Newton iteration method to solve the target angle, realizes unbiased estimation of ADBF generalized monopulse angle measurement, and is suitable for arbitrary multi-beam angle measurement. The application solves by the Newton iteration method, can eliminate the estimation deviation of the conventional generalized monopulse angle measurement algorithm, converges through a small number of iterations, and can greatly improve the multi-channel radar ADBF post-angle measurement precision.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, and specifically to an improved generalized monopulse angle measurement method based on first-order Newton iteration. Background Technology

[0002] Multi-channel active phased array radars employing ADBF (Adaptive Digital Beamforming) technology can effectively suppress sidelobe interference, but this can cause disturbances to the adaptive beam. If traditional monopulse technology is still used in this case, it will lead to angle measurement errors. Generalized monopulse angle measurement technology is an effective way to solve the angle measurement problem after ADBF.

[0003] The current conventional generalized monopulse angle measurement technique is a modified version of the generalized monopulse angle measurement method proposed by Nickel, which is applicable to arbitrary sum and difference beam weighting. However, this algorithm uses partial approximations and has certain limitations:

[0004] 1) The real part of the single-pulse ratio is ignored in the algorithm derivation because, in an ideal situation, the real part of the sum-difference single-pulse ratio is zero. Therefore, the conventional generalized single-pulse angle measurement algorithm is only applicable to sum-difference beams and cannot be directly extended to any number of beams.

[0005] 2) This algorithm is based on the first-order Taylor approximation in the spatial steering vector u and v domains, and its angle measurement accuracy is highly dependent on the linearity of the angle discrimination curve. Studies have shown that in the u and v domains, the sum and difference angle discrimination curves are not strictly linear within the main lobe range of the antenna pattern. In interference environments, with ADBF adaptive weighting, the sum and difference angle discrimination curves become even more unpredictable. Analysis shows that when the target is not at the center of the adaptive beam, the algorithm is a biased estimate with a fixed deviation, such as... Figure 1 As shown. Summary of the Invention

[0006] In view of this, the present invention provides an improved generalized monopulse angle measurement method based on first-order Newton iteration, which can be applied to any multi-beam angle measurement. It is solved by Newton iteration method and can eliminate the estimated offset of conventional generalized monopulse angle measurement algorithm. It can converge after a small number of iterations and can significantly improve the angle measurement accuracy after ADBF of multi-channel radar.

[0007] An improved generalized single-pulse angle measurement method based on first-order Newton iteration includes the following steps:

[0008] Step 1: Calculate the multi-beam ADBF weights and echoes using ADBF technology. The echoes include the sum beam, azimuth difference beam, and elevation difference beam.

[0009] Step 2: Perform target detection on the beam echoes to obtain the target location, and extract all beam target echoes based on the target location;

[0010] Step 3, according to the principle of digital beam forming, a multi-beam angle measurement model based on sum beam, azimuth difference beam and elevation difference beam is established;

[0011] Step 4, a first-order Newton iteration method is used to iteratively calculate the target angle until the iteration result converges, so as to obtain the target angle.

[0012] Further, in step 1, the sum beam echo is S0=g0 H S; the azimuth difference beam S1=g1 H S; the elevation difference beam S2=g2 H S; wherein S is an echo, g0 is an adaptive weight of a sum beam, g1 and g2 are adaptive weights of an azimuth difference beam and an elevation difference beam respectively, and H is a conjugate transpose.

[0013] Further, in step 2, target detection is performed on the sum beam echo to obtain a target position n, and target azimuth difference beam and elevation difference beam echoes are extracted according to the target position;

[0014] The sum beam echo is y0=S0(n);

[0015] The azimuth difference beam and the elevation difference beam echoes are y i i (n)i=1,2.

[0016] Further, in step 3, the multi-beam angle measurement model established is:

[0017]

[0018] wherein R1 and R2 are monopulse ratios, which can be directly obtained from the echo; f0, f1 and f2 are conventional adaptive beam forming functions based on corresponding weights g0, g1 and g2 respectively; v t =sin(θ t ), θ t are the target azimuth angle and the target elevation angle respectively.

[0019] Further, in step 4, the target angle iteration method is:

[0020] A. Initialization: when the iteration number k=1, the target angle is initialized according to the beam pointing direction (u0, v0)

[0021] B. Iterative calculation: according to the formula

[0022]

[0023] iterative calculation is performed until the iteration result converges; wherein g1(u t (k),v​t (k)) represents the ratio of the target first digital beam echo to the digital sum beam at the kth iteration, g2(u t (k),v t (k)) represents the ratio of the target second digital beam echo to the digital sum beam at the kth iteration; g1'(u t (k)) is the value of the partial derivative of the function g1 with respect to u at u = u t (k), v = v t (k), g1'(v t (k), g2'(u t (k)), g2'(v t (k) are obtained in the same way.

[0024] Further, during the iterative calculation, the iteration number and u t , v t are used to determine whether convergence is achieved, if not, the iteration number k is increased by 1 and the iteration is continued; if convergence is achieved, the target angle is calculated by the following formula:

[0025]

[0026] where u t_r , v t_r represent the real parts of u t , v t respectively.

[0027] Compared with the prior art, the present application has the following beneficial effects: the present application establishes a multi-beam ADBF angle measurement model, theoretically deduces a solution algorithm based on first-order Taylor approximation, and finally solves by Newton iteration method to obtain the target angle, thereby realizing unbiased estimation of ADBF generalized monopulse angle measurement. Compared with the conventional generalized monopulse technology, the present application does not have strict and difference beam restrictions, can be applied to arbitrary multi-beam angle measurement, can eliminate the estimation bias of the conventional generalized monopulse angle measurement algorithm by solving by Newton iteration method, and can converge after 2-3 iterations, thereby greatly improving the multi-channel radar ADBF post-angle measurement precision. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description only constitute some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0029] Figure 1 Figure 1 is a diagram showing the estimation bias of the conventional generalized monopulse angle measurement;

[0030] Figure 2A flow chart of the improved generalized monopulse angle measurement method based on first-order Newton iteration in Example 1 or 2.

[0031] Figure 3 A comparison chart of the estimation bias of the method of the present application and the conventional generalized monopulse angle measurement method under near main lobe interference. DETAILED DESCRIPTION

[0032] The embodiments of the present application will be described in detail below with reference to the drawings.

[0033] The above embodiments are only some of the embodiments of the present application, but not all of the embodiments of the present application. The present application can also be implemented or applied through other different specific embodiments, and the details in the specification can be modified or changed based on different views and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0034] Example 1

[0035] Reference Figure 2 An improved generalized monopulse angle measurement method based on first-order Newton iteration includes the following steps:

[0036] Step 1, the ADBF technology is used to calculate the multi-beam ADBF weight and the echo, and the echo includes the sum beam and the azimuth difference beam and the elevation difference beam;

[0037] Step 2, target detection is performed on the sum beam echo to obtain the position of the target, and all beam target echoes are extracted according to the target position.

[0038] Step 3, according to the principle of digital beam forming, a multi-beam angle measurement model based on the sum beam, the azimuth difference beam and the elevation difference beam is established.

[0039] Step 4, the first-order Newton iteration method is used to iteratively calculate the target angle until the iteration result converges, so as to obtain the target angle.

[0040] In the embodiment, firstly, the conventional ADBF technology is adopted to calculate multi-beam ADBF weight and echo; then, the conventional target detection method is adopted to extract the detected target echo; finally, the multi-beam ADBF angle measurement model is established, and the first-order Newton iteration method is adopted to solve, so that the target angle is calculated, the ADBF generalized monopulse angle measurement unbiased estimation is realized. Moreover, the method does not have strict and difference beam restriction, can be applied to arbitrary multi-beam angle measurement, and can eliminate the estimation bias of the conventional generalized monopulse angle measurement algorithm, converges after a small number of iterations, greatly improves the multi-channel radar ADBF post-angle measurement precision; can be applied to the monopulse angle measurement of the multi-channel radar in any beam condition, and has important significance for improving the multi-channel radar ADBF post-angle measurement precision.

[0041] Embodiment 2

[0042] Referring to Figure 2 and Figure 3 , the embodiment takes a one-dimensional linear active phased array radar as an example to detail the process and effect of the improved generalized monopulse angle measurement method based on the first-order Newton iteration method of the application, and the implementation flowchart is as shown in Figure 2 ; the simulation parameters are as follows:

[0043] Radar system parameters: one-dimensional linear active phased array radar, element spacing 0.015m, element number N=60, uniformly divided into M=6 sub-arrays, radar system beam pointing 0°, 200 distance gates in one pulse period;

[0044] Interference parameters: near main lobe interference, interference direction 1°, single element jamming noise ratio JNR=40dB;

[0045] Target parameters: single point signal, target direction value range-1°-0.8°, single element SNR=10dB, in the 30th distance gate;

[0046] The radar echo is S, which is a 6x200 matrix;

[0047] The maximum iteration number K=3.

[0048] Step 1: the multi-beam ADBF weight and echo are calculated by adopting the ADBF technology

[0049] The multi-beam ADBF weight includes:

[0050] a) and beam adaptive weight is g0;

[0051] b) only the target azimuth angle is estimated, and one beam is needed, which is a typical difference beam, and the ADBF weight is g1.

[0052] The multi-beam echo includes:

[0053] a) and beam echo is S0=g0H S;

[0054] b) other beam echoes are S1 = g1 H S.

[0055] Step 2: target detection and extraction of target multi-beam echoes

[0056] Target detection is performed on the sum beam echo and the beam echoes to obtain the target position n = 30. Target multi-beam echoes are extracted according to the target position, including:

[0057] a) the sum beam echo is y0 = S0(n);

[0058] b) other beam echoes are y1 = S1(n).

[0059] Step 3: establishment of a multi-beam angle measurement model

[0060] According to the principle of digital beam forming, a beam angle measurement model is established:

[0061]

[0062] where R1, R2 are single pulse ratios, which can be directly obtained from the echoes; f0, f1, f2 are respectively conventional adaptive beam forming functions based on corresponding weights g0, g1, g2; v t = sin(θ t ), θ t are respectively the target azimuth angle and the target elevation angle.

[0063] Step 4: target angle iteration

[0064] A. Initialization: when the iteration number k = 1, the target angle is initialized according to the beam pointing direction (u0, v0)

[0065] B. Iterative calculation: according to the formula

[0066]

[0067] iterative calculation is performed until the iteration result converges; where g1(u t (k), v t (k)) represents the ratio of the first digital beam echo of the target to the digital sum beam at the kth iteration, g2(u t (k), v t (k)) represents the ratio of the second digital beam echo of the target to the digital sum beam at the kth iteration; g1'(u t (k)) is the partial derivative of the function g1 with respect to u at u = u t (k), v = vt The value of g1'(v) at time (k) t (k), g2'(u) t (k)), g2'(v t (k) Similarly, we can obtain the result.

[0068] Furthermore, during the iterative calculation process, based on the number of iterations and u... t v t Determine if convergence has occurred. If not, increment the iteration count k by 1 and continue iterating. If convergence has occurred, calculate the target angle using the following formula:

[0069]

[0070] Where u t_r v t_r They represent u respectively t v t The real part.

[0071] This embodiment uses the target azimuth angle. The iterative calculation is used as an example for illustration (the pitch angle can be obtained similarly).

[0072] The specific steps are as follows:

[0073] A. Initialize target angle

[0074] Let the iteration number k = 1. At this point, initialize the target angle according to the beam direction u0:

[0075] u t (1)=u0

[0076] B. Newton's iterative generalized single-pulse angle measurement

[0077] Calculate the target angle for the (k+1)th iteration using the following iterative formula:

[0078] u t (k+1)=u t (k)+[g'(u t (k))] -1 [R1-g(u t (k))]

[0079] Where g1(u t (k) represents the ratio of the target's other digital beam echoes to the digital beam echoes at the k-th iteration:

[0080]

[0081] g1'(u t (k) is the partial derivative of function g1 with respect to u, where u = u t The value at (k):

[0082]

[0083] Convergence judgment and calculation of target angle output

[0084] According to the number of iterations and u t The judgment of convergence is that the number of iterations k>K, and convergence is considered.

[0085] a) If there is no convergence, the number of iterations k is added by 1, and the Newton iteration generalized monopulse angle measurement is repeated;

[0086] b) If convergence, the target angle is calculated by the following formula.

[0087]

[0088] Wherein u t_r represents the real part of u t .

[0089] Figure 3 The implementation effect diagram of the application is given, the radar system beam pointing is 0°, the near main lobe interference angle is 1°, and in the case that the target angle is-1°~0.8°, compared with the conventional generalized monopulse angle measurement method, the estimation deviation of the application method after three iterations is obviously less, and the multi-channel radar ADBF post-angle measurement precision is greatly improved.

[0090] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited to this, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An improved generalized single-shot direction finding method based on first order Newton iteration, characterized in that, Comprising the following steps: Step 1, using ADBF technology to calculate multi-beam ADBF weight and echo, the echo comprising sum beam and difference beam in azimuth, difference beam in elevation; Step 2, target detection is carried out on the sum beam echo to obtain the position of the target, and all beam target echoes are extracted according to the target position; Step 3, a multi-beam angle measurement model based on sum beam, difference beam in azimuth and difference beam in elevation is established according to the principle of digital beam forming; Step 4, the first-order Newton iteration method is used to iteratively calculate the target angle until the iteration result converges to obtain the target angle.

2. The improved generalized SPAR method based on first order Newton iteration of claim 1, wherein, Step 1 neutralized beam echo is S0 = g0 H S; azimuth difference beam S1 = g1 H S; elevation difference beam S2 = g2 H S; Wherein, S is echo, g0 is the adaptive weight of sum beam, g1 and g2 are the adaptive weights of difference beam in azimuth and difference beam in elevation respectively, and H is conjugate transpose.

3. The modified generalized SPAR method based on first order Newton iteration of claim 2, wherein, In step 2, target detection is carried out on the sum beam echo to obtain the position n of the target, and target difference beam in azimuth and difference beam in elevation echoes are extracted according to the target position; The sum beam echo is y0=S0(n); Azimuth difference beam, elevation difference beam echo is y i = S i (n)i = 1, 2.

4. The modified generalized SPAR method based on first order Newton iteration according to claim 3, characterized in that, The multi-beam angle measurement model established in step 3 is: Wherein R1, R2 are monopulse ratios, which can be directly obtained according to echoes; f0, f1, f2 are respectively conventional adaptive beam forming functions based on corresponding weights g0, g1, g2; v t = sin (θ t ), θ t are target azimuth angle and elevation angle respectively.

5. The modified generalized SGP method based on first order Newton iteration as claimed in claim 4, wherein, The target angle iteration method in step 4 is: A. Initialization: At iteration number k = 1, the target angle is initialized according to the beam pointing (u0, v0) B. Iterative calculation: according to the formula The iterative calculation is performed until the iteration result converges; wherein g1(u t (k),v t (k)) represents the ratio of the target first digital beam echo to the digital sum beam at the kth iteration, g2(u t (k),v t (k)) represents the ratio of the target second digital beam echo to the digital sum beam at the kth iteration; g1'(u t (k)) is the partial derivative of the function g1 with respect to u, and the value at u=u t (k),v=v t (k); g1'(v t (k), g2'(u t (k), g2'(v t (k) are similarly obtained.

6. The modified generalized SGP method based on first order Newton iteration as claimed in claim 5, wherein, According to the iteration number and u t , v t determine whether it converges, if not, the iteration number k is added 1, and the iteration continues; if it converges, the target angle is calculated by the following formula: where u t_r , v t_r denote the real parts of u t , v t , respectively.

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