This thesis concerns with the localization, tracking, and sensor management in the Multiple-Input Multiple-Output (MIMO) radar systems. The collocated and widely-separated MIMO radars are separately discussed and the signal models are derived for both structures. The first chapter of the thesis is dedicated to the tracking and localization in collocated MIMO radars. A novel signal model is first formulated and the localization algorithm is developed for the derived signal model to estimate the location of multiple targets falling in the same resolution cell. Furthermore, a novel tracking algorithm is proposed in which the maximum bound on the number of uniquely detectable targets in the same cell is relaxed. The performance of the tracking and localization algorithms is finally evaluated using the tracking Posterior Cramer-Rao Lower Bound (PCRLB). After showing the impact of the antennas position on the localization CRLB, a novel sensor management technique is developed for the collocated MIMO radars in Chapter 4. A convex optimization technique is proposed for the antenna allocation in a single-target scenario. When multiple targets fall inside the same cell, a sampling-based technique is formulated to tackle the non-convexity of the optimization problem. The third chapter of this thesis also proposes new approaches for detection, localization, and tracking using a widely-separated MIMO radar. A scenario with multiple-scatterer targets is considered and the detection performance of both MIMO and multistatic radars will be evaluated in the designed scenario. To estimate the location of the multiple-scatterer target, a Multiple-Hypothesis (MH) based approach is proposed where the number and the location of multiple targets are both estimated. A particle filter based approach is also formulated for the dynamic tracking by a widely-separated MIMO radar. Finally, the performance of the MIMO radar and the miultistatic radar in detecting and localizing multiple-scatterer targets is studied.

Doctor of Philosophy (PhD)