{"id":"W7085149061","doi":"10.1109/trs.2025.3618755","title":"Bayesian Nonparametric Tracking of Target Impulse Response for Cognitive Radars","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Radar Systems","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Bayesian probability; Particle filter; Impulse response; Kalman filter; Gaussian; Radar tracker; Monte Carlo method; Bayesian inference; Recursive Bayesian estimation","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001025085,0.0002628892,0.0004693861,0.0008582805,0.0003626568,0.0001686631,0.000673202,0.0001873928,0.00001036663],"category_scores_gemma":[0.00008106326,0.0002580096,0.0002542251,0.001696282,0.00008330913,0.0003358402,0.000004587408,0.0002941613,0.000009819772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009012474,"about_ca_system_score_gemma":0.0001965786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008743349,"about_ca_topic_score_gemma":0.000006458225,"domain_scores_codex":[0.9975357,0.0003850441,0.0006878073,0.0006052734,0.0003769287,0.0004092574],"domain_scores_gemma":[0.9960711,0.002606933,0.0002163151,0.0006995113,0.0002934905,0.000112639],"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":[0.01140528,0.004012905,0.0003003665,0.002045627,0.001963244,0.0001682683,0.004969599,0.2934794,0.01894263,0.01609104,0.0231131,0.6235085],"study_design_scores_gemma":[0.007277344,0.001563842,0.0005847255,0.002571073,0.0003011035,0.0001253393,0.001511853,0.8187038,0.1368142,0.0009836192,0.02809942,0.001463696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004747616,0.0004089432,0.9886947,0.0002057834,0.004282934,0.0008487093,0.0003010028,0.0002386091,0.0002716932],"genre_scores_gemma":[0.9720885,0.00002487799,0.02683173,0.0001163283,0.00005001504,0.00009407977,0.000007009253,0.0000229403,0.0007644759],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9673409,"threshold_uncertainty_score":0.9999872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01522681906581011,"score_gpt":0.271757986238925,"score_spread":0.2565311671731149,"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."}}