Waveform-agile sensing for tracking: A review perspective

In the improvement of sensor performance in applications like sonar, radar, biomedicine, and communications, waveform-agile sensing is fast becoming an important technique. In this technique, waveforms are selected to optimize a tracking performance criterion like minimizing the tracking mean-square error or maximizing target information retrieval. Such waveforms can be designed directly based on their estimation resolution properties, selected from a class of waveforms with different parameter values over a feasible sampling grid in the time-frequency plane. In recent research regarding this matter, it was found that waveforms that maximize the time-bandwidth product do not necessarily provide the best tracking performance and that nonlinear FM chirp waveforms offer significant advantages over linear FM chirp waveforms. They also showed reduced tracking errors and show that dynamic waveform adaption is more effective in the presence of clutter than in clutter-free environments.