Phase comparison monopulse sum-difference phase correction method based on measured data

Abstract

The present invention relates to a method for phase comparison monopulse sum-difference phase correction based on measured data, and belongs to the field of radar parameter estimation. The method includes the following steps: (1) Mix and equally spaced sample the echo signals received by the receiving array, and then perform digital down-conversion. Finally, perform matched filtering to obtain the target echo data at the element level of the left and right sub-arrays; (2) Perform digital beamforming on the left and right sub-arrays respectively; (3) Obtain the sum path and difference path data after matched filtering; (4) Assume that the target is located between two adjacent beams, and obtain the angle estimation value of the target in the left beam and the angle estimation value of the target in the right beam according to the formula. (5) The phase relationship can be solved from the equality of the angle estimation values of the targets in the left and right beams, that is, the sum-difference channel phase difference that needs to be compensated finally. Based on the measured data of the phased array radar, the present invention performs online phase correction on the sum and difference channels, without the need for external injection of test signals, which is efficient and fast.

Description

Technical Field

[0001] The present invention belongs to the field of radar parameter estimation, and specifically relates to a phase correction method for sum-difference angle measurement of a phased array radar. The present invention is used for angle estimation in a phased array radar. Background Art

[0002] The monopulse radar is a new technology germinated in the late 1940s. Since its inception, it has gradually played an increasingly important and irreplaceable role in aviation and missile defense systems, and its high-precision indicators have met the urgent and demanding requirements of many high-precision tracking radars. In theory, the monopulse angle measurement only needs to process one echo pulse to determine the target angle information. In engineering, due to its small computational amount and high angle measurement accuracy, it is a commonly used angle estimation algorithm for phased array radars.

[0003] The schematic diagram of the phase comparison monopulse angle measurement structure of a phased array radar is as Figure 2 shown. When the phased array radar based on phase comparison monopulse angle measurement performs angle estimation, the left half array and the right half array respectively form a left beam and a right beam pointing to the same spatial angle. Note that at this time, the phase centers of N array elements are located at the center of the array. The basic principle of phase comparison monopulse is to form sum and difference beams through the addition and subtraction of the left and right beams. There is a fixed equation relationship between the ratio of the sum and difference two-way target echo data and the angle, and the angle information of the target can be obtained through calculation.

[0004] The angle estimation accuracy of the phase comparison monopulse angle measurement method of a phased array radar is mainly affected by the amplitude and phase inconsistency characteristics of the sum and difference channels. In an actual phased array radar system, there are inconsistencies in amplitude and phase between the sum channel and the difference channel. This inconsistency will directly affect the magnitude of the sum-difference ratio and thus affect the angle measurement result. At present, most of the phase correction methods for sum and difference channels are based on ideal mathematical models, and the phase correction relationship is obtained through offline data processing. The literature "Research on Channel Consistency Calibration Method for Monopulse Radar System" introduces an offline calibration method to correct the amplitude-phase errors of the sum and difference channels of a phased array radar system, and has achieved good calibration results. The measurement error after calibration is within the allowable range of the system accuracy. High accuracy is the advantage of offline calibration, but it requires injecting test signals, so its application is subject to certain limitations. Summary of the Invention

[0005] Technical Problems to be Solved

[0006] In order to avoid the deficiencies of the prior art, the present invention proposes a phase comparison monopulse sum-difference phase correction method based on measured data, which can effectively improve the target angle measurement accuracy.

[0007] Technical Solutions

[0008] A method for phase comparison monopulse sum-difference phase correction based on measured data, characterized by the following steps:

[0009] Step 1: Assume that the phased array is a linear array with a total of N array elements, where N is an even number and the element spacing is d; mix, equally spaced sample, then perform digital down-conversion, and finally perform matched filtering on the echo signal received by the receiving array to obtain the target echo data y of the left and right sub-array elements l and y r y l and y r respectively represent the target pulse compression data of N / 2 channels of the left and right half arrays;

[0010] Step 2: Perform digital beamforming on the left and right sub-arrays respectively to obtain and where a half (θ1) represents the steering vector of the half array, and θ1 represents the beam center pointing;

[0011] Step 3: Obtain the sum path and difference path target data, and where and respectively represent the sum path and difference path data of the target echo after matched filtering;

[0012] Step 4: Assume that the target is located between two adjacent beams, and the left beam center pointing is θ l , according to the formula obtain the angle estimation value of the left beam target; where, φ represents the sum-difference channel phase difference, and λ is the wavelength of the radar transmitted signal;

[0013] Step 5: Assume that the right beam center pointing is θ r , repeat the above steps to obtain

[0014] Step 6: From the equation the phase relationship φ can be solved, that is, the sum-difference channel phase difference that needs to be compensated finally.

[0015] The N = 16.

[0016] A computer system, characterized by comprising: one or more processors, a computer-readable storage medium for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the above method.

[0017] A computer-readable storage medium, characterized by storing computer-executable instructions, which are used to implement the above method when executed.

[0018] A computer program, characterized in that it includes computer-executable instructions, and the instructions are used to implement the above-mentioned method when executed.

[0019] Beneficial effects

[0020] A phase comparison monopulse sum-difference phase correction method based on measured data proposed by the present invention performs online phase correction on the sum and difference channels based on the measured data of the phased array radar, without the need for external injection of test signals, which is efficient and fast. At the same time, the phase correction method proposed by the present invention is based on measured data rather than an ideal laboratory environment, so the phase compensation is more accurate.

[0021] The present invention has the following advantages compared with the prior art: (1) The present invention does not require external injection of test signals, and can perform phase correction on the sum-difference channels of the phased array radar in the field environment, which is efficient and fast; (2) The corrected phase is obtained by real-time processing of measured data, which is more accurate than the ideal environment and has high angle measurement accuracy. Brief description of the drawings

[0022] The drawings are only for the purpose of showing specific embodiments, and are not considered as a limitation to the present invention. Throughout the drawings, the same reference signs represent the same components.

[0023] Figure 1 It is a schematic diagram of the implementation process of the present invention;

[0024] Figure 2 It is a schematic diagram of angle measurement of phase comparison monopulse of phased array radar;

[0025] Figure 3 It is the output of the cost function of the method proposed by the present invention under noisy and noise-free conditions;

[0026] Figure 4 It is the angle measurement accuracy before and after phase compensation of the sum and difference channels by the method proposed by the present invention. Detailed implementation manners

[0027] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0028] Refer to Figure 1 , the specific implementation steps of the present invention are as follows:

[0029] Step 1, mix and equally sample the echo signal received by the receiving array, then perform matched filtering, and finally perform digital down-conversion to obtain baseband data.

[0030] Step 1 specifically includes the following sub-steps:

[0031] (1a) Assume that the phased array is a linear array with a total of N array elements (N is an even number), the element spacing is d, and the wavelength of the transmitted signal is λ. After the received array receives the signal, it performs mixing processing and intermediate frequency sampling. Finally, digital down-conversion is performed to obtain the baseband signals of the target echoes of N channels Its form is

[0032] X = αa(θ t )s(n)+N

[0033] where, [·] T represents the transpose of a matrix or vector. The vector is the target steering vector, θ t is the angle of the target. s(n) represents the waveform transmitted by the phased array radar, the signal length is M, and it satisfies s(n)s H (n)=1. [·] H represents the conjugate transpose of a matrix or vector. N represents the noise matrix, and each element follows a zero-mean Gaussian distribution. α represents the reflection coefficient of the target.

[0034] (1b) Multiply the right side of the above formula by s H (n) to perform matched filtering and then obtain

[0035]

[0036] where, represents the noise after pulse compression. Obtain the left and right half-array data y l and y r .

[0037] Step 2, perform digital beamforming on the left and right sub-array data y l and y r respectively.

[0038] (2a) Perform digital beamforming on y l and y r respectively to obtain and where,

[0039]

[0040] represents θ l represents the phased array radar beam center pointing direction. At this time, the target is assumed to be located between two adjacent beams, that is, θ l < θ t < θ r , d l and dr The target echo after digital beamforming of the left and right half arrays.

[0041] (2b) Without considering the influence of noise, there is

[0042]

[0043] Using the above formula, we get

[0044]

[0045] Among them, is a fixed constant.

[0046] Step 3: Obtain the target data of the sum path and difference path of the left beam, and Among them, and respectively represent the sum path and difference path data of the target echo after matched filtering:

[0047]

[0048] Step 4: According to the obtained sum and difference path data and perform angle estimation.

[0049] (4a) From the above equal relationship, we get

[0050]

[0051] After transformation, the estimated angle is

[0052]

[0053] (4b) Due to the influence of noise and the phase difference between the sum and difference channels, it is necessary to compensate the channel phase. The above angle estimation formula is corrected to obtain

[0054]

[0055] Among them, φ represents the phase difference to be compensated.

[0056] Step 5: Assume that the target is located between two adjacent beams, and the center directions of the two beams are θ l and θ r , that is, θ l <θ t <θ r . Steps 1 to 4 complete the angle estimation of the left beam, and the angle estimation value Repeat the above steps to obtain the right beam target angle estimation value

[0057]

[0058] Among them, and represent the target sum path and difference path data obtained by collecting the right beam.

[0059] Step 6, from the equation the phase relationship φ can be solved, that is, the sum-difference channel phase difference that needs to be compensated finally.

[0060] (6a) When the target is between the two beams, the measured target angles should be the same, so there is the following equation relationship

[0061]

[0062] Define the cost function f(φ)

[0063]

[0064] Finding the minimum value of f(φ) can obtain the phase φ to be compensated, and the subscript i represents the i-th measurement.

[0065] The effects of the present invention can be further illustrated by the following computer simulation experiments and the measured data results of a certain actual system:

[0066] 1. Simulation conditions

[0067] Simulation condition 1, referring to Figure 2 , the phased array radar arrays are all equidistant linear arrays with a half-wavelength, and the number of transmitting array elements N = 16. The target is located at 18°, the center of the left beam points to 17°, the center of the right beam points to 21°, the signal-to-noise ratio is 10 dB, and the phase difference between the sum channel and the difference channel is 20°.

[0068] Simulation condition 2, on the basis of simulation condition 1, the angle measurement accuracy is measured by the root mean square error, and its definition is

[0069]

[0070] Among them, represents the angle estimation value of the k-th Monte Carlo experiment, and θ t represents the true angle of the target. The total number of Monte Carlo experiments is K = 1000. The angle measurement accuracy of the method proposed by the present invention is compared with that without phase compensation.

[0071] 2. Simulation content

[0072] Simulation 1, using simulation condition 1 to obtain the output value of the cost function of the method proposed by the present invention under the noise model and ideal conditions (no noise). Figure 3The output values of the cost function for the method proposed in the present invention under noisy and noise-free conditions are shown. It can be found that even in the presence of noise, the output of the cost function still reaches the minimum value when the compensation phase is 20°, which is consistent with the theoretical value.

[0073] Simulation 2: Analyze the angle measurement accuracy of the method proposed in the present invention before and after phase compensation using Simulation Condition 2. Figure 4 The root mean square error is shown as a function of the signal-to-noise ratio, which varies gradually from 10 dB to 40 dB.

[0074] As can be seen from the figure, the method proposed in the present invention can effectively implement phase compensation for the sum-difference channel of the phased array radar based on measured data. Even under noisy conditions, it can still ensure robustness, and the angle measurement accuracy after phase compensation is significantly improved.

[0075] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should be covered within the protection scope of the present invention.

Claims

1. A method for phase comparison monopulse sum-difference phase correction based on measured data, characterized in that The steps are as follows: Step 1: Assume that the phased array is a linear array with a total of N array elements, where N is an even number and the element spacing is d; mix, sample at equal intervals, then perform digital down-conversion, and finally perform matched filtering on the echo signal received by the receiving array to obtain the target echo data y of the left and right sub-array elements l and y r , y l and y r respectively represent the target pulse compression data of N / 2 channels of the left and right half arrays; specifically: The digital down-conversion obtains the baseband signals of the target echoes of N channels Its form is X = αa(θ t )s(n)+N where, [·] T denotes the transpose of a matrix or vector, and the vector is the target - oriented vector, θ t is the angle of the target, s(n) represents the transmitted waveform of the phased - array radar, the signal length is M, and it satisfies s(n)s H (n)=1, [·] H denotes the conjugate transpose of a matrix or vector, N represents the noise matrix, each element of which follows a zero - mean Gaussian distribution, and α represents the reflection coefficient of the target; Multiply the right side of the above equation by s H After performing matched filtering on (n), we obtain Among them, represents the noise after pulse pressure, obtain the left and right half-array data y l and y r ; Step 2: Perform digital beamforming on the left and right sub-arrays respectively to obtain and where a half (θ1) represents the steering vector of the half array, and θ1 represents the pointing of the beam center; Step 3: Obtain the target data of the sum path and the difference path, sum wherein sum respectively represent the sum path and difference path data of the target echo after matched filtering; Step 4: Assume that the target is located between two adjacent beams, and the pointing direction of the center of the left beam is θ l , according to the formula obtain the angle estimation value of the target in the left beam; where φ represents the phase difference of the sum-difference channel, and λ is the wavelength of the radar transmitted signal; Step 5: Assume that the center of the right beam points to θ r , repeat the above steps to obtain Step 6: From the equation the phase relationship φ can be solved, which is the sum-difference channel phase difference that finally needs to be compensated; specifically: The target is between the two beams, and the measured target angles should be the same. Therefore, there is the following equation relationship Define the cost function f(φ) Finding the minimum value of f(φ) can obtain the phase φ to be compensated. The subscript i represents the i-th measurement.

2. A phase comparison monopulse sum-difference phase correction method based on measured data according to claim 1, characterized in that The aforementioned N = 16.

3. A computer system, characterized in that Including: One or more processors, a computer-readable storage medium for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in claim 1.

4. A computer-readable storage medium, characterized in that Stored with computer-executable instructions, the instructions are used to implement the method described in claim 1 when executed.

5. A computer program product, characterized in that Including computer-executable instructions, the instructions are used to implement the method described in claim 1 when executed.

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