{"id":"W2149525449","doi":"10.1109/taes.2008.4667712","title":"Joint detection and tracking of unresolved targets with monopulse radar","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Monopulse radar; Amplitude-Comparison Monopulse; Radar tracker; Computer science; Particle filter; Radar; Track-before-detect; Artificial intelligence; Algorithm; Continuous-wave radar; Filter (signal processing); Computer vision; Radar engineering details; Radar imaging; Telecommunications","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":[0.001015106,0.0004698414,0.0007190456,0.0004926442,0.0002160056,0.0007730147,0.0006612306,0.0008266412,0.0004217025],"category_scores_gemma":[0.002978517,0.00038939,0.0004046813,0.0005152487,0.0004377288,0.001217429,0.001350855,0.0007821587,0.0003259855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002349404,"about_ca_system_score_gemma":0.0004396662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006187691,"about_ca_topic_score_gemma":0.0006385551,"domain_scores_codex":[0.9992132,0.0001667575,0.00003782327,0.0001681979,0.0003608223,0.00005311656],"domain_scores_gemma":[0.9988415,0.0005756898,0.0001876117,0.0002052368,0.0001533586,0.0000366525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007247943,0.0002649089,0.00360876,0.0001923833,0.000169892,0.0003895796,0.0002759604,0.2669026,0.2204354,0.01441868,0.0009514584,0.4916656],"study_design_scores_gemma":[0.00002452788,0.0001413962,0.001512776,0.000006993933,0.00001912893,0.000205113,0.00001725991,0.9597691,0.0329599,0.00439281,0.0009227556,0.00002825935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04420777,0.0001833975,0.954648,0.00005504088,0.00002077591,0.00002224773,0.00001940939,0.0002104059,0.000632939],"genre_scores_gemma":[0.524048,0.0002815821,0.4730789,0.00006724572,0.00004092354,0.0000634565,0.0001172454,0.00004290244,0.002259722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001015106,"threshold_uncertainty_score":0.005368471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501448935278231,"score_gpt":0.1994032985918094,"score_spread":0.1843888092390271,"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."}}