{"id":"W2990066212","doi":"10.23919/eumc.2019.8910916","title":"Evaluation of Antenna Calibration and DOA Estimation Algorithms for FMCW Radars","year":2019,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Calibration; Computer science; Subspace topology; Antenna (radio); Radar; Algorithm; Direction of arrival; Remote sensing; Antenna array; Electronic engineering; Telecommunications; Engineering; Mathematics; Artificial intelligence; Geology","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":[0.002784311,0.0007941255,0.0006367477,0.0006996975,0.0002632941,0.000622095,0.0006500701,0.0009970474,0.001242965],"category_scores_gemma":[0.01256114,0.000169767,0.0003381423,0.0007749917,0.0003099904,0.001233813,0.0007436345,0.0004878855,0.0003330056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004064562,"about_ca_system_score_gemma":0.0003597723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007480447,"about_ca_topic_score_gemma":0.0005273852,"domain_scores_codex":[0.9983473,0.0006109281,0.00007418322,0.0002134803,0.0006689804,0.00008521751],"domain_scores_gemma":[0.9950674,0.003009523,0.0002459714,0.0003985814,0.001209418,0.00006902087],"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":[0.0005935496,0.0001881953,0.00314072,0.000355992,0.0001674654,0.00005203773,0.0001139124,0.4251304,0.03113424,0.003777682,0.000712292,0.5346335],"study_design_scores_gemma":[0.00005300713,0.0004770953,0.003642222,0.00002992125,0.00004162689,0.0001645776,0.00004788663,0.9603151,0.03297835,0.0009234545,0.001297247,0.00002945309],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1113599,0.000902126,0.8849352,0.00009798796,0.00005544033,0.00006577043,0.00006334377,0.000692756,0.001827492],"genre_scores_gemma":[0.6992211,0.0005690552,0.2981053,0.00005445398,0.00004730849,0.0001125531,0.000269586,0.0001755709,0.00144506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002784311,"threshold_uncertainty_score":0.01472503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03748051387163361,"score_gpt":0.3237691773840559,"score_spread":0.2862886635124223,"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."}}