Wall Clutter Suppression Method Based on Joint Dual-Channel Low-Rank and Sparse Decomposition for UAV-Mounted TTW-SAR

Uncrewed aerial vehicle (UAV)-mounted through-the-wall synthetic aperture radar (TTW-SAR) is critical for urban building detection, holding significant value in civilian and military applications. However, wall clutter is typically much stronger, severely degrading imaging quality. To address this issue, this article proposes a joint dual-channel low-rank and sparse decomposition (JD-LRSD) method for wall clutter suppression based on UAV-mounted TTW-SAR. In the proposed method, a joint dual-channel low-rank and sparse model is developed, with constraints of the dual-channel similarity and wall clutter distribution. Then, the alternating direction method of multipliers (ADMM) is employed to solve the developed optimization problem. Closed-form solutions of each subproblem are derived as explicit expressions. Finally, numerical simulations and field experiments are carried on a dual-channel UAV TTW-SAR system. The proposed method improves the signal-to-interference-plus-noise ratio (SINR), outperforming comparison methods by more than 9 dB.