Radar Signal Retrieval for Multiple Measurement via Iterative Reweighted Approach

Abstract

This work deals with the joint estimation of radar signal waveform and angle in the presence of impulse noise. Firstly, considering spatial sparsity of radar echo signals and multiple measurement vectors (MMV) model, the estimation problem is formulated as an optimization in terms of least-absolute-shrinkage-and-selection-operator (LASSO) form with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\ell_{2.1}+\ell_{2.1})$</tex> -norm minimization. Then, the original problem is transformed into a constrained minimization problem which is more suitable for iterative reweighed technique encouraging sparse solution. Furthermore, one iterative reweighted scheme and Lagrange multiplier technique are employed to solve the optimization problem and get an iterative closed form solution. At last, experimental results show that the proposed algorithm outperforms the state-of-the-art approaches in terms of the convergence rate and steady-state value.