Research On MIMO Radar Parameter Estimation And STAP

Multiple Input Multiple Output(MIMO) radar is a new radar system which transmits detectionsignals via multiple antennas, and also receives echo signals using multiple antennas. Through theapplication of techniques such as waveform diversity, spatial diversity, MIMO radar can obtain bettertarget detection and parameter estimation performance compared to the conventional phased arrayradar. At present, there are two different types of MIMO radar systems: colocated MMIO radar systemand statistical MIMO radar system, the research on MIMO radar mainly includes target detection andparameter estimation, waveform optimization and space-time adaptive processing (STAP) etc. Theproblem of colocated MIMO radar joint estimation of multiple parameter, parameter estimationperformance analysis and MIMO radar space-time adaptive processing (STAP) is considered in thispaper, the main contents are as follows:1. Study the basic principles and system structure of MIMO radar. The signal models ofcolocated MMIO radar are builded. With the time-space structure, two signal models for colocatedMMIO radar are considered, one is parameter estimation signal model, and the other one is theMIMO-STAP signal model when MIMO radar working with down look mode.2. The problem of joint estimation of multiple parameters for MIMO radar is studied. First, theconventional Capon and Apes are extended to angle-Doppler2D domain, a method of joint estimationfor target reflection amplitude, angle and Doppler realized by cascade algorithm is proposed, andsimulation results show that the algorithm can achieve accurate estimation performance simply withengineering and practical significances. Then, for MIMO radar with L-shape array, amulti-dimensional ESPRIT algorithm using multistage wiener filtering (MWF) is put forward, thealgorithm estimates the high dimensional signal subspace by MWF firstly, and then realizes theestimation of target2D angle and Doppler with multi-dimensional ESPRIT algorithm, which reducesthe computational complexity of the algorithm effectively.3. An analysis is performed on target parameter estimation performance. Study the cramer-raobound (CRB) for MIMO radar with uniform linear array and L-shape array. First, the CRB of targetangle estimation with the configuration of uniform linear array and L-shape array are derived, analyzethe influence of transmit signal, element configuration and element spacing on target parameterestimation performance. And the relationship between CRB and2D angle is analyzed for MIMO radarwith L-shape array.4. The knowledge-aided space-time adaptive processing for MIMO radar is studied. A new knowledge-aided STAP algorithm for airborne MIMO radar is proposed. Based on knowledge-aidedMWF structure, the algorithm can greatly reduce the computational complexity and sample needs ofairborne MIMO radar STAP and at the same time keep the performance of clutter suppression bydesigning reasonable constraint matrix and constraint vector through the use of jamming directionknowledge and clutter subspace knowledge estimated by prolate spheroidal wave functions. Also,knowledge-aided effect on the convergence performance when the knowledge is mismatched isconsidered. Simulation results show that when there is a certain error of knowledge, the algorithm canstill effectively improve the convergence performance of STAP algorithm.