An Efficient Time Reversal Technique Based on CSF-MUSIC for Unexploded Ordinances Localization

The time reversal (TR) imaging technique demonstrates favorable positioning accuracy and target discrimination capability, making it well-suited for unexploded ordnance (UXO) detection applications. However, its practical applicability and real-time performance in engineering contexts remain limited due to two primary factors: the requirement for large-scale antenna arrays in conventional TR-based imaging, and the significant computational complexity associated with decomposing the full time reversal operator (TRO). To address these limitations, this paper proposes a common-offset based space-frequency multiple signal classification (CSF-MUSIC) algorithm. The method recon structs the conventional space-frequency multistatic data matrix (SF-MDM) into a novel common-offset SF-MDM (CSF-MDM). Crucially, CSF-MUSIC operates in a dual-antenna measurement mode, which overcomes the fundamental constraint in traditional MUSIC algorithms mandating more antennas than targets, facilitating more compact detection system design. Furthermore, we introduce an optimized iterative QR decomposition to replace conventional singular value decomposition (SVD) for TRO processing derived from CSF-MDM, which reduces the complexity of decomposing the full TRO, substantially reducing computational time. Simulation and experimental results demonstrate that the proposed algorithm enables precise localization and imaging of UXO using a dual-antenna detection system. Compared to conventional TR-based methods, CSF-MUSIC delivers enhanced spatial resolution while reducing computation time by 89%, markedly improving imaging efficiency.