Adaptive waveform scheduling in radar: an information theoretic approach

In this paper, the problem of adaptively selecting radar waveforms from a pre-defined library of waveforms is addressed from an information theoretic perspective. Typically, radars transmit specific waveforms periodically, to obtain for example, the range and Doppler of a target. Although modern radars are capable of transmitting different waveforms during each consecutive period of transmission, it is hitherto unclear as to how these waveforms must be scheduled to best understand the dynamic radar scene. In this paper, a new information theoretic metric - directed information - is employed for waveform scheduling, and is shown to incorporate the past radar returns to effectively schedule waveforms. We formulate this waveform scheduling problem in a Gaussian framework, derive the corresponding maximization problem, and illustrate several special cases.