Wind Turbine Clutter Mitigation for Weather Radar via Low- Rank Matrix Completion

Abstract

The wind turbine clutter (WTC) caused by the rotating blades has become a main factor that limits the detection performance of weather radar. However, none of the conventional clutter mitigation techniques such as interpolation recovery can simultaneously suppress WTC and recover weather information without damage. In this paper, a novel sparse optimization algorithm based on matrix completion is introduced for weather radar WTC suppression. Owing to satisfying the random distribution of missing elements, a low-rank Hankel matrix is firstly constructed, and then, the weather signal can precisely be recovered by Matrix completion using inexact augmented Lagrangian multiplier (IALM) method. The proposed algorithm can effectively suppress not only the WTC but also the noise, and realizes the accurate recovery of the weather signal. An experimental test validates the effectiveness of the proposed MC algorithm.