Research On Multi-Target Angle Estimation Algorithm Based On MIMO Radar

Angle estimation is a key part in target detection.Achieving high-precision angle estimation is helpful for the following target location and tracking.MIMO radar has the characteristics of space,frequency and waveform diversity.It can also use the orthogonality of transmitting waveform to expand the virtual aperture,so as to improve the accuracy of DOA estimation.However,due to the complexity of the actual electromagnetic environment,MIMO radar is confronted with multi-path coherent signals and Gauss color noise,and the classical angle estimation algorithm has high computational complexity and poor real-time performance.These problems restrict the practical application of DOA estimation algorithm in MIMO radar.To this end,this paper conducts in-depth research on these three issues,the main innovations include:Aiming at the invalidation of direction finding algorithm caused by coherent sources in multipath environment,a method of MIMO radar angle estimation based on spatial smoothing and sparse reconstruction is studied.Firstly,the multi-path effect is modeled and analyzed,and the received signal model of MIMO radar in multi-path environment is constructed.Then,the virtual aperture expansion is realized by matched filtering at the receiving array,and the virtual forward-backward spatial smoothing matrix is constructed by using the output signal,thus the covariance matrix is restored to full rank.Then,the covariance matrix is vectorized and sparsely expressed,and the angle estimation problem is transformed into the recovery problem of sparse signals by utilizing the sparseness of the spatial domain of the source.The angle of the target is solved by convex optimization toolkit.Finally,the effectiveness of the algorithm is verified by simulation.Aiming at the performance degradation of classical direction finding algorithm caused by Gauss color noise,a correction angle estimation algorithm based on signal subspace orthogonal projection transform is proposed.Firstly,the limitations of spatial difference algorithm and high order cumulant algorithm under Gaussian colored noise are analyzed.Then,orthogonal projection operator is constructed based on signal subspace to estimate noise covariance matrix and eliminate it,so as to eliminate the influence of Gaussian colored noise.Then,DOA estimation is carried out using the corrected signal covariance matrix.This paper presents an accurate direction finding method in the presence of Gauss colored noise.Compared with the orthogonal projection algorithm based on steering vector,this algorithm reduces DOA estimation once while keeping the accuracy of angle measurement unchanged,so it has lower computational complexity and better real-time performance.Finally,the effectiveness of the algorithm is proved by simulation.Aiming at the problem of high complexity and poor real-time performance of MUSIC algorithm based on MIMO radar,the angle estimation algorithm with reduced complexity for MIMO radar is studied.Firstly,the signal model of monostatic MIMO radar is constructed,and the repeated virtual elements generated by matched filtering of MIMO radar are eliminated by dimension reduction transformation.Then,beam space processing is used to further reduce the computational complexity.Aiming at the problem that the two-dimensional MUSIC algorithm needs two-dimensional peak searching,high computational complexity and poor estimation accuracy under low signal-to-noise ratio(SNR)conditions when DOD and DOA are jointly estimated in MIMO radar,time reversal technology is applied to MIMO radar,and its focusing characteristics are used to multiply the received signal energy.Combining with the characteristics of TR MIMO radar received signal,real value method is used to transform complex domain operations into real domain operations,which reduces the complexity of the algorithm.Then DOD is estimated and substituted into the two-dimensional spatial spectral function to estimate DOA,which transforms the two-dimensional spectral peak search into two one-dimensional spectral peak search,and realizes the automatic matching between DOD and DOA.