{"id":"W2025252188","doi":"10.5194/isprsannals-ii-2-61-2014","title":"Discrete EKF with pairwise Time Correlated Measurement Noise for Image-Aided Inertial Integrated Navigation","year":2014,"lang":"en","type":"article","venue":"ISPRS annals of the photogrammetry, remote sensing and spatial information sciences","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Inertial navigation system; Kalman filter; Extended Kalman filter; Noise (video); Computer science; Filter (signal processing); Artificial intelligence; Computer vision; Epoch (astronomy); Control theory (sociology); Mathematics; Inertial frame of reference; Algorithm; Image (mathematics); Physics","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":[0.0009209992,0.0008926534,0.001187031,0.0005149458,0.0003736909,0.0007978338,0.0009907811,0.001083543,0.001409988],"category_scores_gemma":[0.003291883,0.0004631803,0.0008170133,0.0007464365,0.0005287082,0.001133479,0.000971921,0.001424788,0.0005463845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008205535,"about_ca_system_score_gemma":0.001603419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01064002,"about_ca_topic_score_gemma":0.007149098,"domain_scores_codex":[0.9993607,0.0001252755,0.00004943317,0.000139111,0.0002589747,0.00006648534],"domain_scores_gemma":[0.9991919,0.0003406688,0.00009553997,0.00007864136,0.0002691131,0.00002409191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001766455,0.0000448174,0.001076611,0.0001068803,0.00008075668,0.00009315482,0.00008579878,0.7897961,0.00387368,0.008742782,0.001524924,0.1943978],"study_design_scores_gemma":[0.00001114513,0.00001697541,0.0001447578,0.000006478346,0.00001040854,0.00001830613,0.000004441162,0.9973143,0.0007687344,0.001085459,0.0006120889,0.000006829549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004600872,0.0002026308,0.9945528,0.00004826379,0.00006531068,0.00001431577,0.00002281018,0.0001639856,0.0003291419],"genre_scores_gemma":[0.5017068,0.0006345827,0.49111,0.0001958989,0.000156266,0.0002431219,0.0005841873,0.00009209669,0.005277035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01064002,"threshold_uncertainty_score":0.02115619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02206168512894734,"score_gpt":0.2410284612745404,"score_spread":0.2189667761455931,"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."}}