{"id":"W4318049665","doi":"10.3389/fphy.2023.1134160","title":"Joint DOD and DOA detection for MIMO radar based on signal subspace reconstruction and matching","year":2023,"lang":"en","type":"article","venue":"Frontiers in Physics","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Subspace topology; Signal subspace; MIMO; Computer science; Algorithm; Direction of arrival; Orthogonality; Radar; Noise (video); SIGNAL (programming language); Beamforming; Covariance matrix; Artificial intelligence; Mathematics; Telecommunications; Antenna (radio)","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":[0.0001451704,0.00009951487,0.000147625,0.00009198148,0.00008587603,0.00004655115,0.00002139075,0.00005251988,3.817786e-7],"category_scores_gemma":[0.000005005348,0.0001045722,0.00002427113,0.0001589094,0.0000203093,0.0001351997,0.00000507479,0.0001036254,5.732534e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005164683,"about_ca_system_score_gemma":0.00000741347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001092599,"about_ca_topic_score_gemma":0.00000527529,"domain_scores_codex":[0.9995062,0.00001427831,0.0001204938,0.0001429689,0.00007363892,0.0001424616],"domain_scores_gemma":[0.9998469,0.00002663787,0.00002772416,0.00005699783,0.00001103307,0.0000306913],"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":[0.00007256862,0.00001235568,0.001386284,0.0009254205,0.00004018575,0.000004677257,0.001072881,0.1333268,0.03537942,0.00009732882,0.001744873,0.8259372],"study_design_scores_gemma":[0.0004997944,0.00003992207,0.0005737759,0.0001660632,0.000008988301,0.000003284694,0.0005512728,0.9757649,0.0146813,0.00732492,0.000227359,0.0001583782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.31554,0.0001564832,0.6830336,0.00002615527,0.0007806157,0.0001641627,0.000005684201,0.0001284139,0.0001649232],"genre_scores_gemma":[0.9898598,0.00002045959,0.009859947,0.000009804567,0.0001845358,0.00001697672,0.00000391636,0.00002615807,0.00001837787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8424382,"threshold_uncertainty_score":0.4264332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009982024119593294,"score_gpt":0.1942894849279314,"score_spread":0.1843074608083381,"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."}}