Gridless Sparse Recovery-based Wind Speed Estimation for Wind-shear Detection Using Airborne Phased Array Radar

Abstract

The accuracy of wind speed estimation is an important factor affecting wind-shear detection in airborne weather radar. Aiming at the problem that dictionary mismatch in the sparse recovery-based wind speed estimation leads to the performance degradation, this paper proposes a wind speed estimation method based on atomic norm minimization for airborne array weather radar. The method first constructs joint sparse recovery measurements by compensating multiple array element data with wind-shear orientation information, and then the wind speed is estimated on continuous parameter domain using atomic norm minimization with multiple compensated measurements. Simulation experiments demonstrate that the proposed method can effectively improve the accuracy of wind speed estimation under dictionary mismatch, and the performance is better than that of the existing sparse recovery-based method of wind speed estimation with the pre-set discretized dictionary.