{"id":"W3157878946","doi":"10.1109/lcomm.2021.3074890","title":"Harmonic Retrieval Joint Multiple Regression: Robust DOA Estimation for FMCW Radar in the Presence of Unknown Spatially Colored Noise","year":2021,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Colors of noise; Robustness (evolution); Direction of arrival; Computer science; Noise (video); Algorithm; White noise; Radar; Colored; Gaussian noise; Mathematics; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009113751,0.0001344077,0.0002419295,0.0001820944,0.0001953168,0.00007850576,0.00217442,0.00006819324,0.00000286631],"category_scores_gemma":[0.001232526,0.0001167809,0.0001109422,0.0009851067,0.0002356911,0.0004919907,0.000306759,0.0002173868,0.000002400775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008660536,"about_ca_system_score_gemma":0.000193042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009268086,"about_ca_topic_score_gemma":0.0001033413,"domain_scores_codex":[0.998093,0.0004937089,0.0006372099,0.0002585141,0.0003509326,0.0001666029],"domain_scores_gemma":[0.9950855,0.001477583,0.0004681828,0.002547498,0.0003878469,0.00003333494],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001134179,0.001120578,0.000647719,0.0003010018,0.00008005348,0.00000824383,0.007296199,0.04268607,0.8706665,0.02612081,0.015784,0.03517541],"study_design_scores_gemma":[0.0005670054,0.0000620295,0.002307711,0.0002851247,0.00001859353,0.00001218435,0.00005683623,0.6017458,0.3922867,0.001409337,0.001080718,0.0001679596],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04240694,0.0001886339,0.9302515,0.02587597,0.0002171207,0.000794751,0.00001740148,0.0001190173,0.0001286224],"genre_scores_gemma":[0.545822,0.00005946307,0.4536635,0.0003030941,0.000008790756,0.00009578808,0.0000285532,0.000007391667,0.00001139625],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5590597,"threshold_uncertainty_score":0.4762187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06117261001555043,"score_gpt":0.3014371230762116,"score_spread":0.2402645130606611,"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."}}