MIMO Radar Signal Processing: Target Detection And Angle Estimation

Multiple-Input Multiple-Output (MIMO) radar is a multiple antenna radar system capable of transmitting diverse waveforms simultaneously with its transmitting array and receiving the reflected signals with its receiving array. MIMO radar offers the radar engineers more degrees of design freedom than traditional phased array radar. Fully exploiting these design freedoms can significantly improve target detection, parameter estimation, as well as target tracking and recognition performance. With current advances on MIMO radar signal processing, the dissertation mainly studies MIMO radar signal processing algorithms with special attention on the target detection and angle estimation problems.Main contributions are as follows:1. Study adaptive MIMO radar detectors under clutter with unknown statistical properties. Firstly, a Generalized Likelihood Ratio Test (GLRT) is proposed to improve the detection performance exploiting the spatial diversity of MIMO radar and a MIMO-GLRT detector is developed. The closed expressions for detection probability and false alarm probability are derived. Then, a simplified GLRT is derived with the block diagonal property of clutter covariance matrix to reduce both the computational complexity and the secondary range cell numbers required for clutter covariance estimation. A closed expression of the detection performance is given for the special case of two receiver radar elements. Finally, the GLRT with diagonal loading are suggested to improve the detection performance of MIMO radar in limited secondary data case. The closed-form detection probabilities and false alarm probabilities of the detector are derived. Theoretical analysis and numerical results show the advantages of the proposed detectors.2. Study the sidelobe target suppression and robust target detection for MIMO radar under clutter with unknown statistical properties.Firstly, two adaptive processing schemes are developed and examined to reduce unwanted signals entering the system through sidelobes. The first scheme is the MIMO version of the adaptive beamformer orthogonal rejection test (MIMO-ABORT) method and the second one is the adaptive detector with conic rejection (MIMO-ADCR). The Constant False Alarm Rate (CFAR) properties of the two detectors are demonstrated and their performance are numerically evaluated. The results show that the two detectors can reject sidelobe signals with good performance at the cost of a slight reduction in mainlobe signal detection performance, as compared with MIMO version of Kelly's GLRT (MIMO-GLRT). Secondly, three adaptive processing schemes are developed and examined to improve robustness with respect to steering vector mismatch. At the design stage, the steering vector is assumed to belong to a known linear subspace and a generalized likelihood ratio principle and Rao test criterion are applied. Subsequently MIMO versions of the Subspace Generalized Likelihood Ratio Test (MIMO-SGLRT), the Subspace Adaptive Beamformer Orthogonal Rejection Test (MIMO-SABORT) and the Subspace Rao detector (MIMO-SRao) are developed. The CFAR properties of the three detectors are demonstrated and the performance of the MIMO-SGLRT, MIMO-SABORT and MIMO-SRao detectors in both the matched and mismatched steering vector cases are numerically evaluated. The results show the robustness of the proposed detectors to steering vector mismatch. Thirdly, The MIMO version of an Adaptive Conic Acceptance and Rejection detector (ACARD) is given. It is shown that the detection performance is a function of the cone parameter. With different cone parameters, the detector exhibits different compromise capabilities between sensitivity of mainlobe signal and rejection of sidelobe signal. Also the CFAR property of the detector is derived and numerically evaluated.3. Study the direction of arrical (DOA) estimation problems for MIMO radar under symmetricα-stable (S aS) and compound-Gaussian clutter.Two pre-processing techniques, fractional lower order moment (FLOM) and infinity-norm normalization, are suggested to mitigate the effects of SaS impulsive clutters. Under analyzing the eigenstructure of the preprocessing datda, the FLOM-MUSIC and Inf-MUSIC are suggensted to perform the DOA estimations for MIMO radar. For compound-Gaussian clutter, the theoretical performance of the DOA estimation is studied. The Average Cramer-Rao Bounds (ACRB) and the Outage Cramer-Rao Bounds (OCRB) are derived and their properties are analyzed. The ACRB is further studied for the inverse-Gamma distributed texture component and the OCRB is given as a supplement to the divergence of ACRB when there is only one transmit radar element.4. Study the estimation of the direction of departure (DOD) and DOA of coherent targets for MIMO radar.The covaraince matrix of MIMO radar data with coherent targets is analyzed and its elemet expression is given. A new matrix is constructed. It is demonstrated that the new matrix can be decomposed into signal subspace and noise subspace and the rank of the signal subspace equals to the number of targets. Then the subspace-based techniques can be used to effectively perform the estimaion of DOD and DOA. As an example, the Estimation of Signal Parameters via Rotation Invariant Techniques (ESPRIT) is applied to demostrate the estimation performance.