Fast Reweighted Smoothed l-Norm Near-Field Source Localization Based on Fourth-Order Statistics

The $l_{1}$ -norm-based sparse signal reconstruction has relatively satisfactory performance for near-field parameter estimation. However, its computational complexity is still much higher than that of most other near-field parameter estimation algorithms. In this letter, a reweighted smoothed $l_{0}$ -norm near-field parameter estimation algorithm is proposed based on the fourth-order cumulant statistics (FOC). The direction of arrival (DOA) and range parameters are solved respectively in the reweighted smoothed $l_{0}$ -norm sparse reconstruction method by a steepest ascent method. According to the numerical simulations, the proposed algorithm can achieve low-complexity and fast sparse parameter estimation. Finally the superiority of the proposed algorithm is proved through the comparison of simulation and calculation.