Multiple-Targets Parameter Estimation For MIMO Radar

Multiple Input Multiple Output (MIMO) radar is a new radar system developed recently. Due to applications of spatial diversity, waveform diversity and other new technologies, MIMO radar can obtain better probability of target detection and parameter estimation performance compared to the traditional phased array radar. This paper mianly aims at multiple-targets parameter estimation in MIMO radar system. The completed major tasks are as follows.For bistatic MIMO radar, the joint steering vector is derived, and the multiple signal classification (MUSIC) spectral estimator is constructed to implement the joint estimation of the direction of departure (DOD) and direction of arrival (DOA). Simulation results show that the higher paremeters estimation property of targets is achieved.A method of multi-dimensional parameters joint estimation of bistatic MIMO radars based on time-space structure is put forward. The rotational factors produced by the phrase shifts due to the adjacent delays in time domain and the adjacent transmitting and receiving array elements respectively are utilized, and the multi-dimensional estimation of signal parameters by rotational invariance techniques (ESPRIT) is applied to implement the joint estimation of Doppler, DOD and DOA. Simulation results show that the method outperforms the methods which use the signals'spatial information only, and solve the angle ambiguity problem.A self-calibration approach for MIMO radar with array location uncertainties is proposed. We utilize self-calibration thought and MUSIC estimator to construct a cost function based on genetic algorithms. Simulation results show that the approach provides estimation of DOAs of all the targets as well as calibration on line of the array position error.A robust parameter estimation of Doppler and DOA for MIMO radar is proposed. In a MIMO radar system whose transmitting and receiving array manifolds both have amplitude and phase errors, we utilize the Doppler information to construct a blind adaptive beamformer. Simulation results show that the method can suppress the strong jammer and be more robust to array errors.