{"id":"W2104337872","doi":"10.1049/ip-rsn:20045094","title":"Ground moving target parameter estimation for two-channel SAR","year":2006,"lang":"en","type":"article","venue":"IEE Proceedings - Radar Sonar and Navigation","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Synthetic aperture radar; Azimuth; Computer science; Channel (broadcasting); Remote sensing; Filter (signal processing); Track (disk drive); Inverse synthetic aperture radar; Interferometry; Radar; Geology; Radar imaging; Computer vision; Telecommunications; Physics; Optics","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":[0.000151238,0.0001715093,0.0001465602,0.00007832066,0.0001301348,0.00009318469,0.00006546423,0.00007156596,0.000001486699],"category_scores_gemma":[0.0000239711,0.0001892323,0.00003809496,0.0001221469,0.00003611547,0.0007326454,0.00001448266,0.0001142007,0.000002149887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008702032,"about_ca_system_score_gemma":0.000004959454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002422123,"about_ca_topic_score_gemma":6.517701e-7,"domain_scores_codex":[0.9992124,0.000002304086,0.0002165787,0.0002127752,0.0001301362,0.0002258171],"domain_scores_gemma":[0.9997218,0.00004238329,0.00006177984,0.0000505996,0.00008603268,0.00003737446],"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":[0.0002315059,0.0002237505,0.003857606,0.003937961,0.0001676746,0.00001293127,0.004250464,0.0343837,0.5043951,0.04722266,0.02870969,0.372607],"study_design_scores_gemma":[0.0005588477,0.00005615587,0.0005285911,0.0001627813,0.00002970834,0.00003417442,0.00007087757,0.5938787,0.1416747,0.2600624,0.002556382,0.0003866575],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2981961,0.0004097325,0.6995167,0.00009441807,0.0001006171,0.0004480558,0.00001694973,0.0008983736,0.0003190398],"genre_scores_gemma":[0.6692128,0.000008346876,0.3304546,0.00001906879,0.0001316517,0.00004562979,0.00006271904,0.00003960188,0.00002558293],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.559495,"threshold_uncertainty_score":0.7716671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008333007524375277,"score_gpt":0.2420656921782153,"score_spread":0.23373268465384,"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."}}