Target Localization Of Bistatic Multipleinput And Multiple-output Radar

Bistatic multiple-input and multiple-output（MIMO）radar utilizes a group of transmitting antennas to transmit orthogonal signals,and a group of receiving antennas to collect echo signals from targets.With a large virtual array aperture formed by spatial diversity,bistatic MIMO radar can effectively detect and locate targets.In order to achieve targets location of bistatic MIMO radar,the spatial spectrum estimation algorithm,coherent signal processing,transmission signal design and sparse signal restoration are studied.The main research results can be summarized as follows:Linear prediction（LP）algorithm based on the subspace principle to improve the precise of target location,algorithms based on correlation matrix reconstruction to locate targets under coherent surroundings,transmitted signals based on J orthogonal matrix to improve positioning precise,the joint estimation of 3D parameters of targets in bistatic MIMO radar from sparse signal reconstruction and the improved l₂ norm optimization algorithm to achieve fast target location under dense bins.1.The signal model and related theory of bistatic MIMO radar are studied.Virtual array is discussed based on Minkowski addition and set element subtraction.Under the premise of orthogonal transmitting waveform and matched filtering,the single-target signal model of bistatic MIMO radar is deduced from the transmitting,reflecting and receiving process of electromagnetic wave,and is extended to multi-target signal model.According to the definition of Cramer-Rao bound（CRB）,the CRB for three-parameter of single-object in bistatic MIMO radar and the CRB for three-parameter of multi-objective in bistatic MIMO radar are deduced.As far as multi-parameter estimation in bistatic MIMO radar is concerned,the location precision of LP algorithm decreases.The problem is resolved by subspace principle.2.Anti-diagonal matrix and unitary transformation are used to realize the autopaired direction of departure（DOD）and direction of arrival（DOA）estimation of targets in bistatic MIMO radar,with improved target positioning precise and decreased computational complexity.Based on the autocorrelation matrix and the cross-correlation matrix of received signals,multiple Doppler frequencys are estimated.But it is found that the coherent problem emerges when multiple Doppler frequencys are the same,which causes the rank loss of autocorrelation matrix.Under such circumstances,it is impossible to locate bistatic MIMO radar target directly through eigenvalue decomposition（EVD）.Therefore,based on the idea of matrix reconstruction,diagonal forward space smoothing Estimating Signal Parameters via Rotational Invariance Techniques（DFSS＿ESPRIT）,truncate DFSS＿ESPRIT（TDFSS＿ESPRIT）,Toeplitz-based ESPRIT（Toep＿ESPRIT）and differential space smoothing ESPRIT（DSS＿ESPRIT）are used to solve the rank loss of autocorrelation matrix,and the location of target in bistatic MIMO radar is realized.3.J orthogonal matrix is used to construct the transmitted signal,which improves the positioning accuracy of the target in bistatic MIMO radar.Based on the definition of J orthogonal matrix and the principal pivot transformation,the properties of J orthogonal matrix is analyzed.The effects of unit array,Gaussian matrix,Hadamard matrix and J orthogonal matrix on the CRB of target angles in bistatic MIMO radar are simulated and analyzed.4.Based on a sparse signal reconstruction algorithm,the simultaneous estimation of the 3D parameters of target in bistatic MIMO radar is realized.The traditional spatial spectrum estimation algorithm can only realize estimation of 2D parameters at the same time.The sparse signal restoration algorithm estimates 3D parameters by using the sparse signal model of bistatic MIMO radar and by converting peak search in spatial spectrum into the peak search of reflection coefficient in a complete dictionary.The singular value decomposition is used to solve the inversion problem of a singular matrix.Adaptive Tikihonov algorithm with the iterative step controlled by the residual signal is utilized to estimate the direction of arrival,the direction of departure and the reflection coefficient of targets simultaneously,and the multiple parameters of targets are automatically matched.5.A weighted l₂ norm algorithm is used to realize the automatic 3D parameters estimation of targets in bistatic MIMO radar under dense bins.The algorithm solves the positioning problem under dense bins.Although dense bins help to improve the target location range,the amount of data involved is large and the algorithm converges slowly.In order to solve this problem,a constraint condition is used to construct a new objective function,and the conjugate gradient algorithm is used.The direction of arrival,the direction of departure and the reflection coefficient of targets in bistatic MIMO radar under dense bins are estimated from the perspective of sparse signal reconstruction.Parameters of every target are automatically matched.