An integrated calibration method for interferometer direction finding error in darkroom environment

Abstract

The present invention relates to an integrated calibration method for interferometer direction finding error in a darkroom environment, which includes: using a darkroom scanning frame to measure the phase difference value of each antenna array element relative to a reference channel according to a certain frequency and azimuth step; secondly, setting the system to a full-band self-checking working mode, recording and storing the interferometer receiving channel phase difference data obtained by injecting a self-checking source corresponding to each frequency point according to the same baseline ratio; summing the antenna passive data and self-checking active data of each frequency point in different directions, and then finding the inherent phase difference information of each channel of the interferometer receiver in different azimuths; switching the system to a real-time detection mode, radiating an external frame signal source, and matching the phase difference information actually detected with the above-mentioned pre-stored prior knowledge, if the maximum matching degree exceeds the set threshold, it can be considered that the mapped azimuth meets the direction finding confidence requirement. The method is not only highly operable, but also has the characteristics of high interferometer direction finding calibration accuracy.

Description

Technical Field

[0001] The invention belongs to the field of signal analysis and data processing in interferometer system equipment. Background Art

[0002] With the advancement of science and technology and the rapid development of electronic reconnaissance methods, in the current complex electromagnetic environment, quickly and accurately locking the direction of the radiation source target has become the key to the success of electronic warfare. Compared with the traditional phased array, the interferometer system is limited by the antenna gain and cannot achieve a longer detection distance, but it still has broad application prospects in the field of electronic signal detection due to its advantages of low system complexity and high-precision direction finding.

[0003] At present, the least squares deambiguation algorithm is mainly used to solve the phase difference ambiguity problem in interferometer direction finding equipment. However, after the system error is calibrated, some frequency points will still be ambiguous, affecting the direction finding accuracy. For this reason, a literature proposes a dynamic and static interferometer channel phase calibration method, but the direction finding results after calibration are not analyzed and verified. Summary of the invention

[0004] The present invention proposes an integrated calibration method for interferometer direction finding error in a darkroom environment to achieve accurate calibration problems caused by factors such as radome uniformity, array element coupling, multipath interference, etc. When the inherent phase difference of the system is greatly affected by frequency, incoming wave direction, antenna type and array element arrangement, a full-band multi-angle adaptive calibration method is used to correct the phase difference data, and a confidence evaluation is performed on the direction finding results that meet the threshold, so as to accurately evaluate the direction finding results.

[0005] The present invention provides an integrated calibration method for interferometer direction finding error in a darkroom environment, comprising the following steps:

[0006] Step 1: Test the phase difference of each antenna array element relative to the reference channel in all frequency bands and convert it into the corresponding passive phase error value according to the unambiguous baseline ratio requirement.

[0007] The full-band and all-round division of radar signals is to divide the azimuth grid into different granularities, and adaptively cut the azimuth grid according to the frequency of the radiation signal, so as to accurately measure the system passive error generated by the front-end antenna, thereby ensuring that step 3 traverses the direction-finding value that meets the threshold to the maximum extent.

[0008] Step 2: Record and store the active phase error value of the full-band radar signal when the system works in the self-test mode.

[0009] The active phase error value refers to the error caused by changes in the external environment and performance loss during the use of each channel of the receiver. This part of the error is eliminated by regular calibration of the system self-check source.

[0010] Step 3: Switch the system working mode, calculate the similarity between the actual detected phase difference and the system error, and search for the azimuth corresponding to the maximum matching degree. If the matching degree is greater than the set threshold, it is determined whether it meets the confidence requirement and output the direction finding value. Otherwise, the phase calibration and direction finding of the frequency point data need to be re-performed.

[0011] The similarity calculation refers to the interferometer system using the actual detection phase difference and the system error correlation matching calculation at the frequency point after calibration in steps 1 and 2, and searching for the azimuth corresponding to the maximum matching degree. Once the maximum matching degree reaches the set threshold, the above calculation results need to be evaluated in combination with the confidence criterion, and then go to step 4 to quantitatively analyze the accuracy of the calibration data.

[0012] Step 4: Test the full-band radar signal according to step 3 and compare it with the true azimuth value to calculate the relative root mean square error (RMSE) for quantitative verification and evaluation of the system calibration data and direction finding performance:

[0013] Step 4-1, adopt the control variable method for the direction finding value in step 3, fix the azimuth and frequency radiation signals respectively, record the error between them and the true azimuth, and calculate the relative root mean square error;

[0014] Step 4-2, judge the direction finding statistical results at each frequency point and azimuth in step 4-1, and correctly output the azimuth that meets the direction finding accuracy requirements. Otherwise, repeat the above steps 1-3 until the index requirements are met.

[0015] Furthermore, the system phase error at different azimuth angles in the whole frequency band in step 2 is composed of the passive phase error of the antenna within the range of ±90° at each frequency point and the active phase error in the self-test source sweep mode.

[0016] Furthermore, the mine detection system is set in the real-time detection working mode, and the multi-path phase difference actually detected is converted according to the unambiguous baseline ratio requirement, and the similarity calculation is performed with the system phase error template library in step 3 to solve the corresponding matching degree in each incoming wave direction; if the maximum matching degree exceeds the given threshold, it is judged that it meets the direction finding confidence requirement and the direction finding result is output.

[0017] The beneficial effects of the present invention are: it can realize the calibration of the phase errors of various channels of the interferometer receiver with different wave directions and different frequency points, and has the characteristic of high calibration accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Flowchart of an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The present invention will be further explained below in conjunction with the embodiments and drawings.

[0020] The present invention takes into account that when the interferometer system is actually working, the consistency of phase differences at different frequencies and in various incoming wave directions fluctuates greatly. It is particularly important to adaptively divide the azimuth interval into different granularity calibrations, which can well reduce phase ambiguity and improve direction finding accuracy.

[0021] The process of the embodiment of the present invention is as follows Figure 1 As shown. First, the azimuth grid is divided into coarse and fine granularity according to the calibration frequency band of the radiation source signal, and the N-baseline interferometer direction-finding system is used as an example to illustrate the situation. At a fixed frequency, the darkroom scanning frame is used to measure the phase difference data of each antenna array element relative to the reference channel within the range of ±90° at a certain azimuth step, and a total of M snapshots are generated, that is, the system obtains a total of M groups of azimuth antenna passive calibration values, a total of M*N data, written in the form of the following matrix representation, recorded as matrix A M*N .

[0022]

[0023] The selection of the M value depends on the signal frequency. The M value is adaptively adjusted according to the frequency band. Generally speaking, the higher the frequency, the denser the azimuth sampling points, that is, the larger the M value.

[0024] Secondly, switch the system to the self-test working mode, control the working frequency of the self-test source, and record the active phase error value of the current calibration frequency point, totaling 1*N data, recorded as matrix B 1*N . The matrix A M*N Each row of the passive orientation error value is related to the matrix B 1*N By superposition, the system phase error value at each direction of the current calibration frequency can be calculated, which is recorded as matrix C M*N .

[0025] Then, the system is switched to the real-time detection working mode to actually detect the external radiation signal. After the system is stable, the phase difference measured by the N baseline array elements is recorded as D 1*N , traverse the search and calculate the similarity to find the corresponding matching degree P at each azimuth i (1≤i≤M).

[0026]

[0027] For the calculated P i Sort and filter out P i Maximum value P max The corresponding sequence index Imax, if P max If the value exceeds the set threshold Ω, a linear interpolation algorithm is used to calculate the actual signal's incoming direction θ.

[0028]

[0029]

[0030] θ=-90+Imax·Δθ+δθ

[0031] Due to the influence of external environmental factors, phase jitter is inevitable in actual engineering, so it is often necessary to perform n repeatable tests in different complex electromagnetic environments to ensure the reliability of the calibration data. On this basis, combined with the confidence evaluation criteria, the least square root mean square error RMSE between the actual measurement value and the true value is calculated and evaluated.

[0032]

[0033] Compare RMSE with direction-finding accuracy to determine whether they meet the index requirements, and output the correct direction-finding results for the frequencies and azimuth points that meet the requirements; otherwise, mark them, readjust the azimuth grid adaptively, and perform calibration tests until the calibration accuracy requirements are met.

Claims

1. An integrated calibration method for interferometer direction finding error in a darkroom environment. Features: Step 1: Adaptively divide the azimuth grid into different levels in frequency bands, test the phase difference value of each antenna array element relative to the reference channel, and convert it into the corresponding passive phase error value according to the unambiguous baseline ratio requirement; that is, for the N-baseline interferometer direction-finding system, at a fixed frequency, use the darkroom scanning frame to measure the phase difference data of each antenna array element relative to the reference channel within the range of ±90° at a certain azimuth step, and generate M snapshots in total, that is, the system obtains M groups of azimuth antenna passive phase error values, totaling M*N data, recorded as matrix A M*N ; The selection of M value depends on the signal frequency. According to the frequency band, the M value is adaptively adjusted. The higher the frequency, the denser the azimuth sampling points, that is, the larger the M value; Step 2: Set the system in the self-checking frequency sweeping working mode, record and store the active phase error value of the full-band radar signal, and sum it with the passive phase error data calculated in step 1, and use this value as the system phase error value of the system at different azimuths; Step 3: Set the mine detection system in the real-time detection working mode, convert the multi-path phase difference actually detected according to the unambiguous baseline ratio requirement, and calculate the similarity with the system phase error template library in step 3 to solve the corresponding matching degree in each incoming wave direction; If the maximum matching degree exceeds a given threshold, it is judged that it meets the direction finding confidence requirement and the direction finding result is output; otherwise, the frequency point data needs to be re-phase calibrated and direction found; Step 4: Test the full-band radar signal according to step 3 and compare the actual direction-finding value with the true azimuth value to calculate the relative root mean square error in order to quantitatively verify and evaluate the system calibration data.

2. An integrated calibration method for interferometer direction finding error in a darkroom environment according to claim 1, Features: The system phase error at different azimuth angles in the whole frequency band in step 2 is composed of the passive phase error of the antenna within the range of ±90° at each frequency point and the active phase error in the self-test source sweep mode.

Images