{"id":"W3131547648","doi":"10.1109/taes.2021.3059094","title":"A Maximum Likelihood Method for Joint DOA and Polarization Estimation Based on Manifold Separation","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"National Natural Science Foundation of China","keywords":"Direction of arrival; Antenna array; Azimuth; Polarization (electrochemistry); Algorithm; Computer science; Radar; Mathematics; Antenna (radio); Physics; Optics; 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":[0.001381416,0.001062672,0.0009318051,0.001203974,0.0005658288,0.0007692431,0.001005235,0.0009491705,0.001895982],"category_scores_gemma":[0.005419171,0.0006187771,0.001130216,0.001387118,0.000859131,0.001663285,0.001303216,0.001983137,0.001250765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004394331,"about_ca_system_score_gemma":0.001370575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001770299,"about_ca_topic_score_gemma":0.001570488,"domain_scores_codex":[0.9988487,0.0005024807,0.00005503822,0.0002174148,0.0003218992,0.00005460777],"domain_scores_gemma":[0.9985121,0.0008084049,0.0001409165,0.0001645546,0.0003379537,0.00003601804],"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":[0.0001363311,0.00009669653,0.001245209,0.0001701006,0.0001461232,0.0001210141,0.0002209487,0.4079207,0.01852306,0.06242203,0.003391724,0.505606],"study_design_scores_gemma":[0.000009590934,0.00003235685,0.0002341869,0.000009943934,0.00001045701,0.00008164603,0.00001441116,0.9821101,0.002948518,0.01190902,0.002612468,0.00002734124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005323309,0.00002974384,0.9991832,0.00002060409,0.000005095485,0.000005104819,0.000008732205,0.00008523756,0.000130006],"genre_scores_gemma":[0.06479263,0.0002370768,0.9325876,0.00005868414,0.00007128269,0.00014338,0.0002706056,0.0001450698,0.001693647],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001895982,"threshold_uncertainty_score":0.007305682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01233318553760303,"score_gpt":0.2784506172447646,"score_spread":0.2661174317071615,"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."}}