{"id":"W2035421991","doi":"10.1109/tsp.2013.2274278","title":"Tracking Performance of MIMO Radar for Accelerating Targets","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; MIMO; Radar; Doppler effect; Continuous-wave radar; Low probability of intercept radar; Pulse-Doppler radar; Compensation (psychology); Doppler radar; Radar tracker; Motion compensation; Control theory (sociology); Electronic engineering; Real-time computing; Radar imaging; Algorithm; Telecommunications; Engineering; Physics; Artificial intelligence; Beamforming","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":[0.0008017428,0.000288574,0.0003234442,0.0002669363,0.0001863615,0.0003846548,0.0002378316,0.00040344,0.000505533],"category_scores_gemma":[0.002217203,0.0001265357,0.0001882038,0.0002540195,0.0001358276,0.0003249283,0.0002857728,0.0002556381,0.0002642426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002918989,"about_ca_system_score_gemma":0.0003821846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001317405,"about_ca_topic_score_gemma":0.001063025,"domain_scores_codex":[0.999615,0.00006449169,0.00001421359,0.00005430734,0.0001918046,0.0000602356],"domain_scores_gemma":[0.9987184,0.000562293,0.0001582857,0.0001106818,0.0004046558,0.00004561724],"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":[0.0009542576,0.0001054031,0.009904745,0.0001480356,0.00008544929,0.0001880136,0.0001782265,0.6141982,0.2179223,0.004044293,0.0009023178,0.1513687],"study_design_scores_gemma":[0.00001864734,0.0004168347,0.004830012,0.00000979252,0.00002795659,0.000147029,0.0000220837,0.9526555,0.04088682,0.000539039,0.0004237499,0.00002242458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6999181,0.001043429,0.290848,0.0001644657,0.00008314879,0.00002416857,0.00007040687,0.000606887,0.007241354],"genre_scores_gemma":[0.9855692,0.0001814657,0.01332917,0.00003254068,0.00001097581,0.000005720392,0.00004264481,0.000009145607,0.0008192802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001317405,"threshold_uncertainty_score":0.004240096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02313672106015021,"score_gpt":0.2295071785502782,"score_spread":0.2063704574901279,"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."}}