Sparse reconstruction based direction of arrival estimation of underwater targets

Compressed sensing is a revolutionary paradigm in data acquisition and processing, having impact in several fields. In the complex environment of ocean medium, where early detection of underwater targets is vital, compressed sensing assumes great significance as it brings down the computational resource requirements by reducing the data rates and hardware.In this paper DOA estimation is attempted with a linear array targeting underwater vessels. Array processing is investigated with compressed sensing based techniques and adaptive beam forming. Sparse reconstruction models are developed in this context for signal recovery. Finally the algorithms are validated on a real data set collected from an ocean experiment.