Waveform agile sensing for tracking with collaborative radar networks

In this paper we consider the problem of waveform scheduling for multiple Range-Doppler radars operating collaboratively for target tracking. First, we consider the canonical cases of collocated radar platforms, each capable of choosing a waveform at every PRI from a fixed chirp waveform library. We assume the radars fuse the information that they obtain from their measurements after each chirp pulse in a Kalman Filter tracking framework to obtain posterior distribution of the target state. The radars then use the resulting distribution to jointly select their next waveform set. Our results extend previous work on information theoretic waveform-scheduling proposed for single range-doppler radar to multiple radars interrogating the same target. We show that the radar platforms have to employ a mixture of minimum and maximum chirp-rates supported by the radar hardware to maximize mutual information between the target state and measurements. For the case of two identical radars we completely characterize the optimal combination of chirp waveforms with minimum and maximum chirp-rates as a function of prior target state covariance, carrier frequency, width of transmitting pulse and allowable chirp rates. Finally, the results are extended to arbitrary number of radars at arbitrary geometry.