The detection and tracking of small targets on the ocean surface is a challenging problem due to low signal-to-clutter ratio (SCR) that results from low grazing angles and high sea state. Recent advances in sensing technologies have enabled waveform-agile schemes that tailor the sensor waveform to match the overall sensing objective. In this paper, we propose a methodology to dynamically adapt the transmitted waveform to improve the tracking performance for scenarios characterized by heavy sea clutter. Employing the compound-Gaussfan model for sea clutter, we develop an algorithm for online design of a phase-modulated waveform that improves the SCR in a range bin of interest. A particle filter tracker uses the measurements obtained by this waveform to estimate the target state. We present a simulation study to demonstrate that our scheme leads to improved tracking performance.
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