Study On Parameter Estimation For MIMO Radar

Multiple Input and Multiple Output (MIMO) radar is a new concept of radar which has developed in the international in recent years. Firstly, the paper studies several spectral estimation algorithm for monostatic radar MIMO radar with uniform linear array; Secondly, considering of the adventage of uniform circular array structure, this paper studies the parameter estimation for MIMO radar with uniform circular array; at last, considering of the adventages of Compressive Sensing (CS) tehnology, this paper also studies the parameter estimation for monostatic radar and bistatic MIMO radar with uniform linear array by CS algorithm. The completed major tasks are as follows.This paper studies the MIMO radar system with uniform circular array. Firstly, we derive the model of MIMO radar with uniform circular array and the Cramer-Rao Bound of two-dimension angle estimation for direction-of-arrival, then we estimate the angle direction-of-arrival by the CAOPN algorithm and MUSIC algorithm. Simulation results show that the estimation accuracy of MUISC algorithm is better than CAPON algorithm and we can increase the estimation accuracy by adding the number or circular radius of transmitter/receiver array when the radius of transmitter array is not equal to the radius of receiver array.This paper studies the parameter estimation of monostatic MIMO radar with uniform linear array by Compressive Sensing (CS) algorithm. The received signal of MIMO radar is observed by an observation matrix which is not related to transformation base matrix can be to a lower dimension space, we can resconstructed the original signal highly probability by solving a optimization problem. Simulation results show that the parameter estimation accuracy with CS algorithm of a few datas can be increased by adding the number of transimitter array.This paper studies the parameter estimation for bistatic MIMO radar with uniform linear array by CS algorithm, and a method of optimizing the basis matrix which spans the sparse space for CS algorithm is proposed. This method needs two times estimation for target parameter to be estimated, at the first time, we need to estimate the angle of target roughly to determine the sparse range; at the second time, we need to optimize the basise matrix which spans the sparse space by sparse range to estimate the angle of target accurately. Simulation results show that this method reduces the estimated time of CS algorithm and also increases the accuracy of parameter estimation.