{"id":"W1966718424","doi":"10.1109/taes.2013.6621809","title":"Widely Separated MIMO versus Multistatic Radars for Target Localization and Tracking","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"MIMO; Radar tracker; Computer science; Multistatic radar; Tracking (education); Particle filter; Transmitter; Radar; Signal-to-noise ratio (imaging); Passive radar; Matched filter; Algorithm; Bistatic radar; Filter (signal processing); Electronic engineering; Radar imaging; Engineering; Computer vision; Telecommunications; Beamforming; Channel (broadcasting)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001120514,0.0002014807,0.0002498416,0.00007844954,0.0002364492,0.0002006958,0.00004548256,0.0001081592,0.000008123318],"category_scores_gemma":[0.000003130822,0.000195058,0.00003886974,0.0001499931,0.0000289945,0.0002428908,2.982939e-7,0.0001524226,0.000008127296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001190327,"about_ca_system_score_gemma":0.00003182418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002675493,"about_ca_topic_score_gemma":0.0001151139,"domain_scores_codex":[0.9989843,0.00002990359,0.0002535316,0.000224591,0.0001177401,0.000389907],"domain_scores_gemma":[0.9995925,0.0001034722,0.00004601605,0.0001025881,0.00006381331,0.0000915534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001636513,0.00005491765,0.00003693657,0.001358495,0.0003846236,0.000002084801,0.001526711,0.9331207,0.04315116,0.000326238,0.001930134,0.01794434],"study_design_scores_gemma":[0.001529969,0.0002515928,0.00001154175,0.0001520528,0.00004803291,0.00002170389,0.0007246598,0.9876625,0.006976323,0.00004894677,0.002281303,0.0002913672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1168116,0.002746893,0.8788295,0.00005304272,0.0006071092,0.0006955803,0.00001069748,0.0001616542,0.00008393406],"genre_scores_gemma":[0.9989879,0.0001959519,0.0002584202,0.00001611035,0.00004533747,0.0001658998,0.000004150823,0.00004888956,0.000277366],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8821763,"threshold_uncertainty_score":0.7954236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.011687078596803,"score_gpt":0.2229123510074435,"score_spread":0.2112252724106405,"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."}}