MIMO radar resource allocation using posterior Cramér-Rao lower bounds

A technique is presented that will determine an efficient set of transmitters in a MIMO radar event based on tracking accuracy and energy consumption. The posterior Cramér-Rao lower bound (PCRLB) will provide the means of determining these optimal transmitters by placing a bound on the variance of the track state estimate. This is a predictive PCRLB since it is calculated before any measurements are taken. Optimal transmitters are chosen by minimizing a proposed cost function that incorporates the PCRLB, along with number of transmitters in the MIMO event. To account for measurement origin uncertainty, an information reduction factor (IRF) will be incorporated in the calculation of the PCRLB for each predicted measurement. Since the complexity of the cost calculation increases exponentially with the number of sensors, several approximations are made for the calculation of the PCRLB and IRF. The jacobian matrix for the sine space measurement equations are derived for use in the calculation of the PCRLB. This resource allocation scheme is evaluated using the GTRI/ONR MIMO Radar Benchmark with metrics including track completeness ratio and total cumulative energy consumption.