Dynamic Control of Radar Systems Using Information Rate

We motivate and derive a method of dynamically controlling radar systems by using an approximation of the rate of information produced by repeatedly estimating parameters of a dynamic target. The estimation information rate is given by approximating dynamic source compression of estimated radar target parameters. We use this metric to dynamically manage radar system and spectral resources by setting radar parameters to achieve a minimum, constant, or optimized predicted target information. This approach naturally results in an information-theoretic target scheduling algorithm and radar system resource allocation scheme based on target information instead of heuristic methods. We generalize Bayesian/Kalman radar filtering by adding a target information prediction step. Since information gain is at the heart of radar measurements, any new or unexpected scenarios are easily handled by this metric of control.