A quality control method based on interferometer angle measurement
By combining the remainder theorem and the improved Kalman filtering algorithm, the phase fuzzy problem in high-precision electronic detection direction detection is solved, and the interferometer angle measurement with high precision and high reliability is realized, which is suitable for electronic detection direction detection in dynamic environments.
Patent Information
- Application Number
- CN202411905170.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-23
- Publication Date
- 2025-04-01
AI Technical Summary
The prior art has phase fuzzy problems in high-precision electronic detection direction detection, especially under the influence of noise interference and rapidly changing target signals in dynamic environments, the measurement error is large, and the defuzzy value is prone to errors.
Combining the phase defuzzy technology of the remainder theorem and improving the Kalman filtering algorithm, dynamically optimizes the Kalman gain and covariance by monitoring angle changes in real time, eliminating outliers, and improving angle measurement accuracy and reliability.
The balance between high-precision measurement and maximum non-fuzzy angle is achieved, the accuracy and reliability of the interferometer angle measurement is improved, the calculation amount is reduced, and the real-time requirement is met.
Smart Images
Figure CN119738772A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the technical field of electronic detection and direction finding, and in particular to a quality control method based on interferometer angle measurement. Background Art
[0002] Cross-shaped four-element array interferometers are often used for high-precision target angle measurement, especially for electronic reconnaissance and radar direction finding. In order to measure radar signals, the interferometer frequency range is wide and the baseline length satisfies the staggered relationship. In practical applications, since the interferometer can only measure the phase difference within the range of (-π, π], phase ambiguity exists.
[0003] Phase deambiguation technology solves the contradiction between high-precision measurement and maximum unambiguous angle by analyzing the relationship between baseline length and phase difference. In real-time detection systems, the phase deambiguation method of the remainder theorem uses the specific relationship of baseline length to quickly and in real time calculate the angle ambiguity value, but the correct deambiguation operation of the remainder theorem requires high parameter measurement accuracy. In a dynamic environment, although the remainder theorem deambiguation can accurately calculate most angles, it is affected by noise interference and measurement errors of rapidly changing target signals, and the deambiguation value is prone to errors, so this application has limitations.
[0004] Aiming at the shortcomings of the existing technology, an innovative angle measurement quality control method is proposed. The phase deambiguation technology of the remainder theorem is combined with an improved Kalman filter algorithm. According to the law of the angle change rate under low maneuverability platform, the angle measurement accuracy and reliability of the interferometer are further improved through real-time monitoring and dynamic optimization of Kalman gain and covariance. Summary of the invention
[0005] In order to solve the above technical problems, the present invention provides a quality control method based on interferometer angle measurement, comprising the following steps:
[0006] Step S1: First, calculate the instantaneous phase of the output signal of each channel receiver, then select a channel as a reference channel, and find the phase difference between other output channels and the reference channel;
[0007] Step S2: Use the remainder theorem technique to quickly and effectively deambiguate the phase difference measured by the interferometer to obtain a preliminary angle value;
[0008] Step S3: The defuzzified angle is subjected to an improved Kalman filter algorithm;
[0009] Step S4: monitor the angle value after defuzzification in real time to determine whether the angle change is in line with expectations. If the angle change exceeds the set threshold, remove the abnormal angle value and dynamically update the angle estimate to improve the measurement accuracy.
[0010] In one embodiment of the present invention, step S2 eliminates ambiguity by using the proportional relationship of multiple baselines and the constraint of integer fuzzy quantities, thereby obtaining a unique solution, specifically:
[0011]
[0012] The length of the short baseline is d1, the length of the long baseline is d2, the interferometer measures the phase difference of the short baseline as φ1, and the phase difference of the long baseline as φ2;
[0013] The lengths of the two baselines satisfy the proportional relationship:
[0014]
[0015] And the real phase value φ'1=φ1+2Kπ and φ'2=φ2+2Lπ, K is the real ambiguity number of the phase value measured by the short baseline, and L is the real ambiguity number of the phase value measured by the long baseline.
[0016] In one embodiment of the present invention, the unambiguous range of the phase difference measured by the original baseline phase interferometer is expanded, and the deambiguation process is cleverly performed by adding an additional phase interferometer, and K and L that meet the minimum error are selected, so that Minimum ambiguity resolution, but due to the existence of angle measurement errors, especially near the critical value of (-π, π], there will be errors in the values of K and L.
[0017] In one embodiment of the present invention, in step S3, the improved Kalman filter is used to update in real time to ensure that the angle change conforms to the angle change rate, and the state equation Respectively represent the azimuth angle, pitch angle and their rate of change; according to the current state and state transfer matrix, predict the state and its covariance at the next time, and calculate the Jacobian matrix H of the dynamic observation + ,According to the real-time measurement value, the system state is updated by combining the predicted value and the Kalman gain to optimize the angle estimation.
[0018] In one embodiment of the present invention, in step S4, the angle value after defuzzification is monitored in real time to determine whether its change is in line with expectations; if the angle change exceeds the set threshold, when the residual exceeds the threshold, the weight is dynamically corrected, and the weight factor w is determined according to the distribution relationship between the prediction result and the measured value:
[0019]
[0020] The measured value is θ and the predicted value is σ is the threshold; the weight matrix is adjusted according to the residual, thereby affecting the weighting of the observation noise covariance matrix and finally outputting a high-precision angle measurement result.
[0021] Compared with the prior art, the above technical solution of the present invention has the following advantages: the interferometer angle measurement quality control method of the present invention solves the angle of the two-dimensional cross array baseline in one dimension, uses the remainder theorem to quickly and effectively resolve the ambiguity, reduces the amount of calculation, and meets the real-time requirements. At the same time, the improved Kalman filter algorithm is used to correct some abnormal values, quickly eliminate abnormal values, and improve the accuracy of angle measurement. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments of the present invention in conjunction with the accompanying drawings.
[0023] Figure 1 It is a flow chart of the control method of the angle measurement quality of the interferometer of the present invention;
[0024] Figure 2 is a model diagram of the two-dimensional array surface described in the present invention;
[0025] Figure 3 is a design flow chart of the improved Kalman filter of the present invention;
[0026] Figure 4 It is a diagram showing the effect of the interferometer angle measurement control of the present invention. DETAILED DESCRIPTION
[0027] This embodiment provides a quality control method based on interferometer angle measurement, which can measure the angle of the interferometer quickly and accurately in real time. The phase deambiguation technology based on the remainder theorem can quickly resolve the ambiguity, increase the constraint conditions, reduce the amount of calculation, solve the phase ambiguity problem in the interferometer angle measurement process, and achieve a large range and high-precision preliminary angle estimation. Then, the improved Kalman filter algorithm is introduced to optimize the angle value after deambiguation and eliminate the influence of noise. Finally, through real-time monitoring and dynamic optimization, abnormal angle values are eliminated to further improve the reliability of the measurement results; Figure 1 As shown, the following steps are included:
[0028] Step S1: First, the instantaneous phase of the output signal of each channel receiver can be calculated, and then a channel is selected as a reference channel to find the phase difference between other output channels and the reference channel.
[0029] Step S2: Use the remainder theorem technique to quickly and effectively deambiguate the phase difference measured by the interferometer to obtain a preliminary angle value.
[0030] Step S3: The deblurred angle is subjected to an improved Kalman filter algorithm.
[0031] Step S4: monitor the angle value after defuzzification in real time to determine whether the angle change is in line with expectations. If the angle change exceeds the set threshold, remove the abnormal angle value and dynamically update the angle estimate to improve the measurement accuracy.
[0032] In one embodiment of the present invention, step S2 utilizes the proportional relationship of multiple baselines and the constraint of integer fuzzy quantities to eliminate fuzziness, thereby obtaining a unique solution.
[0033] The short baseline length is d1, the long baseline length is d2, the interferometer measures the phase difference of the short baseline φ1, the phase difference of the long baseline is φ2, the algorithm model reference Figure 2 .
[0034]
[0035] The lengths of the two baselines satisfy the proportional relationship
[0036]
[0037] The true phase values φ'1 = φ1 + 2Kπ and φ'2 = φ2 + 2Lπ, where K is the true ambiguity number of the phase value measured with a short baseline and L is the true ambiguity number of the phase value measured with a long baseline.
[0038] The unambiguous range of the phase difference measured by the original baseline phase interferometer is expanded, and the deambiguation process is cleverly performed by adding an additional phase interferometer, and K and L that meet the minimum error are selected to make Minimum ambiguity resolution, but due to the existence of angle measurement error, there will be errors in the values of K and L near the critical value of (-π, π].
[0039] In one embodiment of the present invention, in step S3, Figure 3 Use improved Kalman filter to update in real time to ensure that the angle change conforms to the angle change rate, state equation Respectively represent the azimuth angle, pitch angle and their rate of change. According to the current state and state transfer matrix, predict the state and its covariance at the next time, and calculate the Jacobian matrix H of the dynamic observation + ,According to the real-time measurement values, combined with the predicted values, the Kalman gain and filter covariance are updated to optimize the angle estimation.
[0040] In one embodiment of the present invention, in step S4, the angle value after defuzzification is monitored in real time to determine whether its change is in line with expectations. When the residual exceeds the threshold, the weight is dynamically modified, and the weight factor is determined according to the distribution relationship between the prediction result and the measured value.
[0041]
[0042] The measured value is θ and the predicted value is σ is a threshold value, and in the present invention, the threshold value is 0.5. The weight matrix is adjusted according to the residual, thereby affecting the weighting of the observation noise covariance matrix, and finally outputting a high-precision angle measurement result.
[0043] In summary, after the above processing of the interferometer angle measurement quality control, the accurate angle measurement function of the interferometer is realized.
[0044] In order to verify the feasibility of this design method, the angle measurement verification is carried out in a microwave darkroom with the help of the existing hardware platform. The design verification scenario is as follows:
[0045] 1) Set the radiation source A to be 10m away from the interferometer and stand still;
[0046] 2) Align the interferometer with the radiation source and rotate the interferometer to simulate the low-speed flight platform test. The interferometer rotates at a constant speed of ±40 degrees. The angle of the radiation source relative to the interferometer is measured through the phase difference.
[0047] 3) Interferometer angle measurement: the accuracy of angle measurement can be verified by checking whether the relative angle after angle control is consistent with the rotation angle.
[0048] The processing effect is shown in the figure Figure 4 As shown, a comparison chart showing the angle measurement results and angle control effect of the interferometer for frequency 3G radiation source and frequency 7G radiation source.
[0049] pass Figure 4 It can be seen that in this embodiment, the interferometer fast angle measurement uses the phase difference to determine the deambiguated angle through the remainder, which is the corresponding measurement value. It can be seen that the measured values after the angle is deambiguated are mostly accurate and change at a constant speed of plus or minus 40 degrees. However, the above deambiguation method will have individual outliers. By improving the Kalman filter correction, the angle value is quickly corrected according to the estimated value and the measured value, and the weight is fused. The corrected angle is close to the angle of the turntable simulated rotation, which reduces the error and improves the angle measurement accuracy.
[0050] Obviously, the above embodiments are merely examples for clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from these are still within the protection scope of the invention.
Claims
1. A quality control method based on interferometer angle measurement, characterized in that: The steps include: Step S1: First, calculate the instantaneous phase of the output signal of each channel receiver, then select a channel as a reference channel, and find the phase difference between other output channels and the reference channel; Step S2: Use the remainder theorem technique to quickly and effectively deambiguate the phase difference measured by the interferometer to obtain a preliminary angle value; Step S3: The defuzzified angle is subjected to an improved Kalman filter algorithm; Step S4: monitor the angle value after defuzzification in real time to determine whether the angle change is in line with expectations. If the angle change exceeds the set threshold, remove the abnormal angle value and dynamically update the angle estimate to improve the measurement accuracy.
2. The quality control method according to claim 1, characterized in that: Step S2 uses the proportional relationship of multiple baselines and the constraint of integer fuzzy quantity to eliminate fuzziness, thereby obtaining a unique solution, which is specifically: The length of the short baseline is d1, the length of the long baseline is d2, the interferometer measures the phase difference of the short baseline as φ1, and the phase difference of the long baseline as φ2; The lengths of the two baselines satisfy the proportional relationship: And the real phase value φ'1=φ1+2Kπ and φ'2=φ2+2Lπ, K is the real ambiguity number of the phase value measured by the short baseline, and L is the real ambiguity number of the phase value measured by the long baseline.
3. The quality control method according to claim 2, characterized in that: The unambiguous range of the phase difference measured by the original baseline phase interferometer is expanded, and the deambiguation process is cleverly performed by adding an additional phase interferometer, and K and L that meet the minimum error are selected to make Minimum ambiguity resolution, but due to the existence of angle measurement errors, especially near the critical value of (-π, π], there will be errors in the values of K and L.
4. The quality control method according to claim 1, characterized in that: In step S3, the improved Kalman filter is used to update in real time to ensure that the angle change conforms to the angle change rate, and the state equation Respectively represent the azimuth angle, pitch angle and their rate of change; according to the current state and state transfer matrix, predict the state and its covariance at the next time, and calculate the Jacobian matrix H of the dynamic observation + ,According to the real-time measurement value, the system state is updated by combining the predicted value and the Kalman gain to optimize the angle estimation.
5. The quality control method according to claim 1, characterized in that: In step S4, the angle value after defuzzification is monitored in real time to determine whether its change is in line with expectations; if the angle change exceeds the set threshold, when the residual exceeds the threshold, the weight is dynamically corrected, and the weight factor w is determined according to the distribution relationship between the prediction result and the measured value: The measured value is θ and the predicted value is σ is the threshold; the weight matrix is adjusted according to the residual, thereby affecting the weighting of the observation noise covariance matrix and finally outputting a high-precision angle measurement result.