{"id":"W2772525328","doi":"10.1007/978-3-319-65283-2_17","title":"Multi Sensor Fusion Based on Adaptive Kalman Filtering","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Fast Kalman filter; Extended Kalman filter; Kalman filter; Alpha beta filter; Control theory (sociology); Invariant extended Kalman filter; Covariance intersection; Ensemble Kalman filter; Unscented transform; Computer science; Sensor fusion; Adaptive filter; Algorithm; Artificial intelligence; Moving horizon estimation","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":[0.00029003,0.0005605975,0.0006618949,0.0005422721,0.0002236811,0.0008858762,0.0007321862,0.0008761642,0.002874248],"category_scores_gemma":[0.0005673441,0.0003733362,0.0006190652,0.001086423,0.0003749731,0.001530408,0.00087222,0.001154367,0.001477736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003767312,"about_ca_system_score_gemma":0.0002306696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007794849,"about_ca_topic_score_gemma":0.0008146127,"domain_scores_codex":[0.9996818,0.00004157706,0.00001738948,0.00007796859,0.000164706,0.00001649054],"domain_scores_gemma":[0.9998605,0.00006184406,0.00001143713,0.00002561929,0.00003641569,0.000004121992],"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":[0.0001038799,0.00004755537,0.000230089,0.0004763916,0.000119795,0.00008859637,0.0001155678,0.1150206,0.04037834,0.07712277,0.01078892,0.7555075],"study_design_scores_gemma":[0.00001134664,0.00007648905,0.0006732869,0.00008430614,0.00005921538,0.0003000719,0.00002255245,0.878971,0.01646297,0.04766271,0.05562487,0.00005113709],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001385947,0.006564512,0.9830505,0.0001326831,0.0004269718,0.00001456733,0.0000314627,0.0004748933,0.007918574],"genre_scores_gemma":[0.2704414,0.02233354,0.6601521,0.0004098818,0.0009374423,0.0001335418,0.0003678474,0.0002876935,0.0449366],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002874248,"threshold_uncertainty_score":0.009615362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05115253728855293,"score_gpt":0.2573293331360518,"score_spread":0.2061767958474988,"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."}}