{"id":"W1966960822","doi":"10.1109/taes.2006.1642587","title":"Passive geolocation and tracking of an unknown number of emitters","year":2006,"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":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Multilateration; Geolocation; Estimator; Solver; Kalman filter; Computer science; Algorithm; Tracking (education); Assignment problem; Smoothing; Nonlinear system; Mathematical optimization; Mathematics; Artificial intelligence; Statistics; Computer vision","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":[0.0004209242,0.0005400005,0.0006903589,0.0004480648,0.0004417236,0.0007547307,0.001430703,0.0009538775,0.001579309],"category_scores_gemma":[0.001283913,0.0004492992,0.0004624664,0.0007222556,0.0004701373,0.001331511,0.001063118,0.0007734884,0.0009843967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004274228,"about_ca_system_score_gemma":0.0009847727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001427107,"about_ca_topic_score_gemma":0.00186392,"domain_scores_codex":[0.9997179,0.0000386081,0.00001635896,0.0001149227,0.00008457237,0.0000275708],"domain_scores_gemma":[0.9996465,0.0001030112,0.00006335236,0.00006774468,0.00009998017,0.00001933568],"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":[0.0001824553,0.00008063178,0.001590064,0.0001317865,0.00003502553,0.0001018605,0.0002357549,0.254638,0.04754441,0.03967102,0.003087308,0.6527016],"study_design_scores_gemma":[0.00002821901,0.00009748327,0.000610952,0.00001426531,0.00001351643,0.000219223,0.00004235266,0.9657738,0.0137992,0.01142811,0.007957223,0.00001567285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002330201,0.00003310823,0.9969324,0.00002741166,0.00001597142,0.00001170091,0.00001276212,0.0001839171,0.0004526417],"genre_scores_gemma":[0.09795781,0.0001305833,0.8964954,0.00005455911,0.00002986176,0.0001580949,0.0001253205,0.00003531256,0.005013007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001579309,"threshold_uncertainty_score":0.005283356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005924293804778403,"score_gpt":0.2234630187557182,"score_spread":0.2175387249509398,"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."}}