Research On Angle Estimation Algorithms For Low Angle Tracking In Array Radar

The tracking of low-angle target is one of the most difficult problems in radar.Due to the influence of the curvature of the earth and the occlusion of the terrain,the effective distance of radar detecting low-altitude targets decreases.Moreover,for modern radar,the performance of low-angle target altitude measurement is limited by multipath phenomenon.The existence of multipath signal makes the performance of radar estimating elevation angles unable to meet the requirements of actual application.In severe cases,the radar may lose its ability to track targets.How to overcome the angle measurement error caused by multipath signal is the key to solving the low-angle tracking problem.Array super-resolution technology has been extensively studied and discussed due to its high direction of arrival(DOA)estimation accuracy,and it has also been used to solve the low-angle tracking problem.Combined with the advantages of the array radar in this thesis,super-resolution DOA estimation algorithms will be mainly researched to realize the high-accuracy measurement of the target elevation in the low-angle tracking field.Firstly,this thesis introduces two geometric models in multipath scene,and gives some geometric relations in the two models.Moreover,the theories of specular and diffuse reflection are illustrated in detail.Then,some super-resolution algorithms are introduced,which include the multiple signal classification(MUSIC)algorithm,the spatial smoothing algorithm and the maximum likelihood(ML)algorithm.The performance of these algorithms are analyzed by simulations,which further elaborates their advantages and disadvantages.Then,based on the multipath signal model,the generalized MUSIC algorithm and its improved algorithm are presented.The angle estimation performance of the two algorithms are compared by simulations.Simultaneously,three temporal-spatial sequential maximum likelihood algorithms are summarized and concluded,and the theoretical error results of their angle estimation are given.The angle estimation performance,which is influenced by the signal-to-noise ratio(SNR)and height of targets are evaluated.Under the same conditions,the three algorithms exploit more and more priori information for angle estimation,which further improve the angle estimation accuracy.Simulation results validate the effectiveness of these algorithms.Simultaneously,the refined maximum likelihood(RML)algorithm is further studied.Considering the problems in practical application,the RML algorithm has been optimized by some feasible means.Finally,this thesis proposes a new low-elevation angle estimation algorithm based on beam-space.Ensuring the accuracy of angle measurement,the proposed algorithm greatly reduces the computational complexity,which is advantageous to the engineering realization.The simulation results also validate the superior performance of the proposed method.