Direction of arrival tracking using adaptive robust subspace decomposition and Kalman filter
Zineb Bekhtaoui, Abdelkrim Meche, Karim Abed‐Meraim, Mohamed Dahmani · 2023
In this paper, we consider directions of arrival estimation and tracking in a noisy and relatively adverse scenario. We thus use a robust subspace tracking method called HTFAPI that exploits a weighted least squares criterion to enhance robustness, followed by a smoothing Kalman filter to improve the estimation. Simulated experiments are then presented to show that the proposed solution enhances the performance when dealing with corrupted data in an impulsive noise environment.