Tracking multiple unresolved targets using MIMO radars

Multiple Input Multiple Output (MIMO) radars are a new generation of radar systems that may bring about many benefits compared to traditional phased-array and multistatic radars. Although different aspects of MIMO radars have been discussed in the literature, the application of MIMO radars in target tracking problems has not been explored in depth. Target localization using MIMO radars with co-located antennas has been discussed in the literature. The main limitation of those approaches is that the number of targets that can be uniquely localized in one cell is restricted. This paper presents a new application of MIMO radars in Multi-Target Tracking (MTT) problems. The main contribution is to show that the use of prior information about the motion of targets relaxes the limitation on the number of targets that can be uniquely detected. A general MTT problem with several targets in the same resolution cell is considered. The goal is to propose a technique to estimate targets' states and the number of targets in one cell. Because multiple targets may fall in the same cell, the measurement in a cell is associated with more than one target. Measurements are outputs of matched filters and range bins that are nonlinear functions of targets' states. Multiple hypotheses are generated based on the uncertainty in target-to-cell association. Then, the best model which gives the number of new targets whose estimates are obtained by the localization algorithm, is selected according to its likelihood . Finally, due to the nonlinearity in measurement model, a UKF based method is used to update estimates of new targets and initialize new born targets. Simulation results show the superiority of the proposed method for joint localization and tracking compared to the previous localization approach suggested in the literature for unresolved targets.