Adam Goad, Austin Egbert, Angelique Dockendorf, C. Baylis, A. Martone, R. Marks
{"title":"Optimizing Transmitter Amplifier Load Impedance for Tuning Performance in a Metacognition-Guided, Spectrum Sharing Radar","authors":"Adam Goad, Austin Egbert, Angelique Dockendorf, C. Baylis, A. Martone, R. Marks","doi":"10.1109/RADAR42522.2020.9114669","DOIUrl":null,"url":null,"abstract":"Transmitter power amplifier load impedance impacts the transmitted power of the radar, which affects the maximum detection range. In spectrum sharing radars, the operating frequency is expected to change on the order of a few milliseconds coherent processing interval (CPI), which can be in the low milliseconds. While a high-power impedance tuner has been developed for radar applications, its reconfiguration time requires at least several hundreds of milliseconds, thus significantly exceeding the CPI time scale and preventing configuration adjustments within the CPI. We demonstrate an algorithm that assesses and improves the amplifier impedance tuning during a spectrum sharing metacognition process in a cognitive radar. Measurement results show success in achieving maximum average power over test intervals using the control of an adaptive software-defined radio platform.","PeriodicalId":125006,"journal":{"name":"2020 IEEE International Radar Conference (RADAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Radar Conference (RADAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR42522.2020.9114669","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Transmitter power amplifier load impedance impacts the transmitted power of the radar, which affects the maximum detection range. In spectrum sharing radars, the operating frequency is expected to change on the order of a few milliseconds coherent processing interval (CPI), which can be in the low milliseconds. While a high-power impedance tuner has been developed for radar applications, its reconfiguration time requires at least several hundreds of milliseconds, thus significantly exceeding the CPI time scale and preventing configuration adjustments within the CPI. We demonstrate an algorithm that assesses and improves the amplifier impedance tuning during a spectrum sharing metacognition process in a cognitive radar. Measurement results show success in achieving maximum average power over test intervals using the control of an adaptive software-defined radio platform.