{"id":"W7127324493","doi":"10.23919/isap63122.2025.11362222","title":"Adaptive Radar Cross Section Reduction via Active Nulling Using LCMV Beamforming","year":2025,"lang":"","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Radar cross-section; Reduction (mathematics); Beamforming; Adaptive beamformer; Radar; Clutter; Flexibility (engineering); Adaptive filter","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002483866,0.0007042204,0.0002575124,0.0003175079,0.0001917239,0.0004691017,0.0004250678,0.0004263178,0.002819],"category_scores_gemma":[0.0005645994,0.0001653816,0.0003333506,0.0003547984,0.0003354686,0.0005973533,0.0006396467,0.0003653374,0.001010516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002850963,"about_ca_system_score_gemma":0.0003718463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002567373,"about_ca_topic_score_gemma":0.0005135812,"domain_scores_codex":[0.9997771,0.00003109995,0.000008239559,0.00002834679,0.0001352088,0.00002003043],"domain_scores_gemma":[0.9997392,0.00009930607,0.00004042756,0.00003086568,0.00007843794,0.0000118232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001978672,0.0001120724,0.0009682642,0.0001736557,0.00004793198,0.0001407979,0.0001830011,0.06680596,0.7222304,0.02632462,0.001611159,0.1812043],"study_design_scores_gemma":[0.00004980327,0.0002711138,0.0009211405,0.00003962235,0.00003019889,0.0004448855,0.00006302409,0.5548137,0.422381,0.006915225,0.01400761,0.00006263432],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03009806,0.0001389036,0.9614732,0.00008918124,0.00003145682,0.00003336683,0.00004913459,0.0004907491,0.007595993],"genre_scores_gemma":[0.3990648,0.0003238405,0.5921652,0.000191014,0.0000421479,0.0001497014,0.0002513168,0.0001869672,0.007624986],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002819,"threshold_uncertainty_score":0.009430528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744249444299745,"score_gpt":0.2657232351555482,"score_spread":0.2482807407125508,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}