{"id":"W2157902093","doi":"10.1109/taes.2010.5461642","title":"Spacial Extrapolation-Based Blind DOA Estimation Approach for Closely Spaced Sources","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Extrapolation; Direction of arrival; Algorithm; Autoregressive model; Rotational invariance; Mean squared error; Snapshot (computer storage); Mathematics; Estimation theory; Computational complexity theory; Computer science; Statistics; Antenna (radio); Telecommunications","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":[0.0005480662,0.0008518476,0.0007502338,0.0007925822,0.0003624047,0.0004374407,0.0007645666,0.0006671348,0.001200088],"category_scores_gemma":[0.001867758,0.0003492351,0.0007035375,0.0005742307,0.0003880428,0.001131983,0.0009723207,0.0007266084,0.0007473044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002446483,"about_ca_system_score_gemma":0.0005898918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008513267,"about_ca_topic_score_gemma":0.001298183,"domain_scores_codex":[0.9995701,0.0001067658,0.00003034283,0.00008333984,0.0001874158,0.00002202345],"domain_scores_gemma":[0.9993327,0.0002772995,0.00008315113,0.000127653,0.0001540307,0.00002511939],"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":[0.0003125146,0.00009768573,0.0008263694,0.000241254,0.0001353041,0.0002300115,0.0002110046,0.2965373,0.1013838,0.0202762,0.001906142,0.5778424],"study_design_scores_gemma":[0.00002090385,0.00008174507,0.0004080434,0.00001632447,0.00003344535,0.0002809726,0.00001693037,0.970959,0.01738615,0.006474781,0.004271007,0.00005069514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002193841,0.00008805968,0.9971469,0.00001562922,0.00001650206,0.000006559044,0.000009244962,0.0001826564,0.0003406193],"genre_scores_gemma":[0.10401,0.0003930023,0.8932621,0.00007272758,0.00008193561,0.00005929866,0.000115596,0.0000668419,0.001938477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001200088,"threshold_uncertainty_score":0.004014671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01311654610750987,"score_gpt":0.2558073252983287,"score_spread":0.2426907791908188,"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."}}