Research On Joint Range-Angle Estimation Methods Of FDA-MIMO Radar Based On Sparse Arrays

Frequency array(FDA)radar as a new type of radar,was proposed by American scholar P.Antonik and others in 2006.Different from traditional radar,the transmit antenna array of FDA radar adopts frequency diversity technology,and each of the transmitting elements has artificially added an orderly frequency increment.The introduction of the frequency increment makes the beam of frequency-diverse array radar is range-angle related.The combination of FDA radar and MIMO technology forms FDA-MIMO radar,which is a new radar mechanism and has received extensive attention in recent years.Target range-angle parameter joint estimation is the key to FDA-MIMO radar target location,while the parameter estimation accuracy and resolution are important indicators of parameter estimation.The main influencing factors are array aperture,snapshot number and signal bandwidth,etc.In the traditional FDA-MIMO radar target location problem,most antenna arrays are configured as uniform linear array.A uniform linear array which has M elements can locate M-1 targets at most.Sparse arrays are new types of antenna arrays put forward in recent years,including coprime Array,nested array,etc.Unlike traditional uniform linear arrays,sparse arrays can achieve larger virtual array apertures through array optimization when they have the same number of physical array elements as a uniform linear array,resulting in better parameter estimation performance.However,in the array optimization process of sparse arrays,the problem of the rank deficiency of the signal is caused.The classical method to solve this problem is the spatial smoothing,however spatial smoothing will sacrifice the partial array aperture,causing a decline in the estimation performance of radar parameters.The compressed sensing algorithm proposed in recent years can effectively solve the problem of rank deficiency caused by sparse array optimization without sacrificing array aperture.Therefore,based on compressed sensing theory and sparse array(coprime arrayand nested array),the joint range-angle estimation of FDA-MIMO radar methods are deeply studied in this paper.The innovative work is as follows:Firstly,the antenna arrays of static FDA-MIMO radars are configured as coprime arrays and nested arrays,respectively,and the corresponding frequency increment is configured as coprime frequency increment and nested frequency increment.Two new monostatic FDA-MIMO radars are proposed---coprime frequency interval coprime array FDA-MIMO radar and nested frequency interval nested array FDA-MIMO Radar.Based on the above signal models,a joint range-angle estimation method based on two-dimensional spatial smoothing MUSIC(2D-SSMUSIC)algorithm is proposed.Compared with the traditional uniform linear array FDA-MIMO radar,the array aperture of the two new radar models is larger and the resolution of parameter estimation is higher.Then,aiming at rank deficiency caused by sparse array equivalence and array aperture reduction caused by spatial smoothing technology,a joint range-angle estimation method for sparse array FDA-MIMO radar target based on two-dimensional orthogonal matching pursuit(2D-OMP)is proposed.Based on the tool of compressed sensing theory,2D-OMP algorithm using coprime arrays and nested array as antenna arrays can effectively solve the problems of subspace method.The simulation results show that the proposed algorithm has higher estimation accuracy and target resolution than the traditional subspace algorithm.Finally,aiming at the computational complexity problem in 2D-OMP algorithm,a joint range-angle estimation method for FDA-MIMO radar target based on two-dimensional stagewise orthogonal matching pursuit(2D-StOMP)is proposed.2D-StOMP algorithm is based on contraction iteration and compressed sensing theory.Compared with traditional algorithms,it has higher parameter estimation accuracy and target resolution.Compared with the 2D-OMP algorithm,it has lower time complexity with similar estimation accuracy.