{"id":"W4212855149","doi":"10.23919/oceans44145.2021.9705878","title":"Kalman Filter-based Doppler Tracking and Channel Estimation for AUV Implementation","year":2021,"lang":"en","type":"article","venue":"OCEANS 2021: San Diego – Porto","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Doppler effect; Computer science; Estimator; Kalman filter; Control theory (sociology); Multipath propagation; Channel (broadcasting); Acoustics; Mach number; Telecommunications; Mathematics; Physics; Statistics; Artificial intelligence","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":[0.0001501393,0.0001461702,0.000170937,0.00006489202,0.0001221261,0.0001155446,0.00009549014,0.00005730534,0.0002846299],"category_scores_gemma":[0.000003981449,0.0001590554,0.00006109891,0.000126943,0.00001392283,0.000183303,0.00002775906,0.00007007442,0.000007765689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004577327,"about_ca_system_score_gemma":0.00002701125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001724127,"about_ca_topic_score_gemma":0.0002737513,"domain_scores_codex":[0.9991256,0.00002977182,0.000315305,0.0001961866,0.0001206611,0.0002125023],"domain_scores_gemma":[0.99946,0.00005216768,0.00005846299,0.0002786857,0.00008092478,0.00006977687],"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":[0.0001043037,0.0004129466,0.01752282,0.002640505,0.0008539184,0.00008628095,0.01445833,0.06624205,0.1557044,0.002471952,0.0890389,0.6504636],"study_design_scores_gemma":[0.004053846,0.0001757604,0.01440747,0.0003005084,0.0001944328,0.00007276158,0.007543346,0.6140428,0.2358395,0.001458355,0.1206672,0.001244079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.446405,0.001479288,0.547419,0.0008499841,0.0003270074,0.0008932952,0.0002301594,0.0003893467,0.002006945],"genre_scores_gemma":[0.9927317,0.00004079914,0.006134322,0.00009980272,0.00008404018,0.00007623385,0.0006392152,0.00004090583,0.000153007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6492195,"threshold_uncertainty_score":0.6486089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02866538188812671,"score_gpt":0.2738017841467935,"score_spread":0.2451364022586667,"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."}}