DOA estimation algorithm based on compressed sensing in HF sky-surface wave radar

High frequency sky-surface wave radar (HFSSWR) utilizes sky-wave transmission and surface-wave receiving to implement further range detection, which proposes the higher requirements for angle estimation precision with few array elements and single snapshot. According to the spatial sparseness of receiving targets, compressed sensing (CS) could high probability recover absent channel signals and obtain accurate target azimuth information. Commonly, continuous parameter region need to be divided into finite discrete grid points for building redundancy dictionary base. However, the grid density is limited by the computational complexity and restricted isometry property, so the direction of arrival (DOA) of the targets usually may be not on the initialized sampling grid in practical situations, which would lead to angle estimation mismatch. In this paper, a novel polar interpolation direction estimation (PIDE) algorithm based on CS was proposed to obtain higher precision with single snapshot and sparse receiving array. The results of numerical experiment based on the measured and simulative data demonstrate the advantage of the proposed algorithm.