{"id":"W2168375507","doi":"10.1109/lsp.2011.2152393","title":"Joint DOD and DOA Estimation for MIMO Array With Velocity Receive Sensors","year":2011,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"MIMO; Direction of arrival; Joint (building); Computer science; Sensor array; Constraint (computer-aided design); Algorithm; Pairing; Key (lock); Mathematics; Telecommunications; Engineering; Channel (broadcasting); Antenna (radio); Physics","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":[0.0005499998,0.0006821479,0.0006306854,0.0004796974,0.0002655922,0.0005868258,0.0003412196,0.0004556283,0.0006204761],"category_scores_gemma":[0.003284188,0.0004004303,0.0003699303,0.0005302264,0.0003436713,0.0009227106,0.0006595493,0.0005293059,0.0003400892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002139404,"about_ca_system_score_gemma":0.0004598504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009054297,"about_ca_topic_score_gemma":0.001272994,"domain_scores_codex":[0.9995696,0.0001168903,0.00003194389,0.0001000708,0.0001413361,0.00004014977],"domain_scores_gemma":[0.9990249,0.0005538742,0.0001367891,0.0000941148,0.0001580932,0.0000322117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003671624,0.00006381105,0.003213451,0.0002218948,0.0001195181,0.000170138,0.0001962015,0.4312476,0.0455382,0.02810076,0.001629459,0.4891318],"study_design_scores_gemma":[0.00002263107,0.00009534744,0.0009473095,0.00001555572,0.0000242754,0.0001724508,0.00004322197,0.9801322,0.008959902,0.007179797,0.002380748,0.00002657848],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01025338,0.0002212855,0.9887717,0.00005288138,0.00002829697,0.000006993546,0.00002235328,0.00009389182,0.0005491269],"genre_scores_gemma":[0.3844843,0.000756769,0.6118048,0.00007875793,0.0001462144,0.000052347,0.0002239357,0.00005130681,0.002401666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009054297,"threshold_uncertainty_score":0.002908707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03297963045655949,"score_gpt":0.2480927040236721,"score_spread":0.2151130735671126,"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."}}