{"id":"W1970595529","doi":"10.1109/radar.2014.7060340","title":"Waveform optimization for random-phase radar signals with PAPR constraints","year":2014,"lang":"en","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Waveform; Clutter; Computer science; Radar; Matched filter; Phase (matter); Electronic engineering; Interference (communication); SIGNAL (programming language); Radar systems; Filter (signal processing); Power (physics); Moving target indication; Pulse-Doppler radar; Algorithm; Telecommunications; Engineering; Radar imaging; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002396683,0.0001211794,0.0001949239,0.00004127339,0.0000732395,0.00006034116,0.00005677555,0.0000497582,0.0001551504],"category_scores_gemma":[0.00001890155,0.0000851971,0.00003619803,0.00006674341,0.00003111208,0.0001570202,0.00000309653,0.00004266075,0.000005108965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001875654,"about_ca_system_score_gemma":0.00001413847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003567054,"about_ca_topic_score_gemma":0.000002889342,"domain_scores_codex":[0.9993916,0.00001029658,0.0002003499,0.0001128505,0.0001047746,0.0001801673],"domain_scores_gemma":[0.9996856,0.00007303829,0.0000314695,0.00008995108,0.00005422152,0.00006568105],"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":[0.0002130577,0.000041668,0.00001222011,0.0004709193,0.00010827,0.000002924274,0.0002700739,0.8674018,0.00984516,0.001676627,0.00205673,0.1179005],"study_design_scores_gemma":[0.005255261,0.0001207898,0.00000109674,0.00006676438,0.00001730017,0.00001263809,0.00008229846,0.9828246,0.008501155,0.00009381468,0.002842634,0.0001816463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005822057,0.00005683089,0.9735304,0.00002766175,0.00008803211,0.0003097579,0.000005379889,0.0002116918,0.01994822],"genre_scores_gemma":[0.9610133,0.000002877374,0.03853574,0.00004779637,0.0001109416,0.00002558557,0.0000149378,0.00003103294,0.0002178449],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9551912,"threshold_uncertainty_score":0.3474237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008238271766593709,"score_gpt":0.2171670623955982,"score_spread":0.2089287906290045,"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."}}