{"ID":2823743,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.24889","arxiv_id":"2512.24889","title":"Adaptive Clutter Suppression via Convex Optimization","abstract":"Passive and bistatic radar systems are often limited by strong clutter and direct-path interference that mask weak moving targets. Conventional cancellation methods such as the extensive cancellation algorithm require careful tuning and can distort the delay-Doppler response. This paper introduces a convex optimization framework that adaptively synthesizes per-cell delay-Doppler filters to suppress clutter while preserving the canonical cross-ambiguity function (CAF). The approach formulates a quadratic program that minimizes distortion of the CAF surface subject to linear clutter-suppression constraints, eliminating the need for a separate cancellation stage. Monte Carlo simulations using common communication waveforms demonstrate strong clutter suppression, accurate CFAR calibration, and major detection-rate gains over the classical CAF. The results highlight a scalable, CAF-faithful method for adaptive clutter mitigation in passive radar.","short_abstract":"Passive and bistatic radar systems are often limited by strong clutter and direct-path interference that mask weak moving targets. Conventional cancellation methods such as the extensive cancellation algorithm require careful tuning and can distort the delay-Doppler response. This paper introduces a convex optimization...","url_abs":"https://arxiv.org/abs/2512.24889","url_pdf":"https://arxiv.org/pdf/2512.24889v1","authors":"[\"Yifan He\",\"Griffin Kearney\",\"Makan Fardad\"]","published":"2025-12-31T14:35:23Z","proceeding":"math.OC","tasks":"[\"math.OC\"]","methods":"[]","has_code":false}