Exploiting Agile Waveforms and Sampling for Compressive Sensing Radar

The goal of the present proposal is to identify and demonstrate enhanced, efficient radar imaging and applications exploiting modern waveform generation. In addition, MIMO beam formation for robust compressive sensing in Maritime applications such as small craft detection and imaging is also proposed. Compressive Sensing has emerged in recent years as a potentially feasible mathematical tool and framework for efficient data collection. However, few active air-to-surface surveillance systems currently exploit the full potential of compressive sensing by probing the ground with fully randomized or partially randomized waveforms. While complete randomization may be impractical, modern digital radar systems are capable of synthesizing a wide variety of modulated waveforms, enabling a more complete and efficient exploration of the time-frequency-angle space over the radar system"s path than has been feasible with current methods. Similarly, MIMO radar systems could introduce randomized beam patterns that introduce variations in the angular distribution of signal over targets in each range bin. Finally, an additional layer of randomization and efficient data reduction may be achieved digitally on board the aircraft by weighting and combining pulses over the aperture path before downlink. In this context sparsity based agile waveform design methods are discussed.