{"id":"W2118286408","doi":"10.1109/radar.2005.1435918","title":"Pre-filtering for clutter rejection in beamspace STAP","year":2005,"lang":"en","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Clutter; Space-time adaptive processing; Computer science; Jamming; Adaptive filter; Signal processing; A priori and a posteriori; Radar; Algorithm; Moving target indication; Filter (signal processing); Doppler effect; Computer vision; Constant false alarm rate; Artificial intelligence; Interference (communication); Continuous-wave radar; Radar imaging; Telecommunications; Physics","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":[0.0003676611,0.0005333229,0.000364272,0.0004935801,0.0003732567,0.0006383972,0.000450921,0.0007936697,0.002688779],"category_scores_gemma":[0.001412496,0.0002664487,0.0004607493,0.0005769232,0.0003997126,0.0007397414,0.0005667374,0.0007461359,0.001569976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001643484,"about_ca_system_score_gemma":0.0005876906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003650591,"about_ca_topic_score_gemma":0.001114489,"domain_scores_codex":[0.9996089,0.00008104069,0.00001708437,0.00004887339,0.0002010196,0.00004306646],"domain_scores_gemma":[0.9995912,0.0001858488,0.00003250233,0.00007067938,0.0001052128,0.00001454992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004289736,0.0001233704,0.0006365762,0.0001798253,0.00005422933,0.0001339931,0.0001174338,0.02954069,0.3010008,0.02701942,0.001619366,0.6391454],"study_design_scores_gemma":[0.00008391171,0.0005655335,0.002866992,0.00005046959,0.00005838678,0.000848643,0.00006590666,0.6429485,0.3079823,0.02466785,0.01978732,0.00007411449],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007622586,0.0001486722,0.9908943,0.0000414004,0.00003672898,0.00001268833,0.00001395751,0.0002576451,0.0009720325],"genre_scores_gemma":[0.1353923,0.0004633742,0.8603452,0.0001611422,0.00008590562,0.00007766591,0.0001406342,0.0001013427,0.003232296],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002688779,"threshold_uncertainty_score":0.008994818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00940819262382118,"score_gpt":0.2280457359871164,"score_spread":0.2186375433632952,"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."}}