Guide vector correlation and local focusing combined angle measurement method

Abstract

The invention discloses a guide vector correlation and local focusing combined angle measurement method, and the method can improve the angle measurement performances and reduce the calculation burden. The method comprises the following steps: receiving a signal through an array antenna, and constructing a received signal guide vector through a phase difference measurement value of the received signal; dividing primary search grid points at a set second step in an angle measurement range of the antenna array, carrying out the correlation matching search of the received signal guide vector anda local reference signal guide vector corresponding to the primary search grid point at each primary search grid point, and obtaining an initial estimation value of angle measurement; taking the initial estimation value of angle measurement as the center, setting an angle search range, carrying out the dividing at a set second step to obtain secondary search grid points, carrying out the correlation matching search of the received signal guide vector and a local reference signal guide vector corresponding to the secondary search grid point at each secondary search grid point, and obtaining a final estimation value of angle measurement, wherein the set second step is shorter than the set first step.

Description

technical field [0001] The invention relates to the technical field of microwave radar measurement, in particular to an angle measurement method combining steering vector correlation and local focusing. Background technique [0002] In the field of space rendezvous and docking radar measurement, space target angle measurement is an important function of rendezvous and docking radar. There are several types of angle measurement methods for radar measurement: interferometer phase comparison method, subspace angle measurement method, subspace fitting angle measurement method, and compressive sensing based angle measurement method. [0003] In September 2011, Han Yuetao proposed a successive recursive solution based on phase difference vector average fuzzy method. In this method, vector average is carried out on the measured values ​​of phase difference at various levels measured multiple times, and the estimated value of phase difference after vector average is used to perfor...

AI Technical Summary

Problems solved by technology

In this method, vector average is carried out on the measured values ​​of phase difference at various levels measured multiple times, and the estimated value of phase difference after vector average is used to perform successive recursive defuzzification angle measurement. This method can improve the estimation accuracy of phase difference in the process of defuzzification. But it will cause recursive errors to propagate step by step, and even lead to errors in the defuzzification algorithm

[0004] In 2013, Wang Tiedan et al. proposed a compressed sampling matching tracking method based on the article "DOAestimation of coherently distributed sources based on block-sparse constraint with measurement matrix uncertainty" on pages 1-8 of the 6th issue of the journal "IEICE Electronics Express". Improved block sparse signal matching pursuit method, which has good robustness, but in the case of low SNR, due to the increase of non-zero elements in sub-blocks, the angle measurement performance of this method drops sharply

This method has good angle measurement performance, but under non-ideal conditions such as low signal-to-noise ratio and small number of snapshots, the angle measurement effect is not good

[0007] Considering the above angle measurement methods comprehensively, there is no angle measurement method that can effectively solve the angle measurement error accumulation problem of the successive recursive de-phase ambiguity method, improve the angle measurement performance under low signal-to-noise ratio, and reduce the amount of calculation

Images