Information Theoretic Physical Waveform Design with Application to Waveform-Diverse Adaptive-on-Transmit Radar

Information theory provides methods for quantifying the information content of observed signals and has found application in the radar sensing space for many years. Here, we examine a type of information derived from Fisher information known as Marginal Fisher Information (MFI) and investigate its use to design pulse-agile waveforms. By maximizing this form of information, the expected error covariance about an estimation parameter space may be minimized. First, a novel method for designing MFI optimal waveforms given an arbitrary waveform model is proposed and analyzed. Next, a transformed domain approach is proposed in which the estimation problem is redefined such that information is maximized about a linear transform of the original estimation parameters. Finally, informationally optimal waveform design is paired with informationally optimal estimation (receive processing) and are combined into a cognitive radar concept. Initial experimental results are shown and a proposal for continued research is presented.