Adaptive High-Resolution Sensor Waveform Design for Tracking (Synthesis Lectures on Algorithms and Software in Engineering)

Recent innovations in modern radar for designing transmitted waveforms, coupled with new algorithms for adaptively selecting the waveform parameters at each time step, have resulted in improvements in tracking performance. Of particular interest are waveforms that can be mathematically designed to have reduced ambiguity function sidelobes as their use can lead to an increase in the target state estimation accuracy. Moreover, adaptively positioning the sidelobes can reveal weak target returns by reducing interference from stronger targets.

The manuscript provides an overview of recent advances in the design of multicarrier phase-coded waveforms based on Bj÷rck constant-amplitude zero-autocorrelation (CAZAC) sequences for use in an adaptive waveform selection scheme for multiple target tracking. The adaptive waveform design is formulated using sequential Monte Carlo techniques that need to be matched to the high resolution measurements.

The work will be of interest to both practitioners and researchers in radar as well as to researchers in other applications where high resolution measurements can have significant benefits.