Matthew B. Heintzelman;Daniel B. Herr;Charles A. Mohr;Shannon D. Blunt;Cenk Sahin;Andrew Kordik
{"title":"Separability Analysis of Random FM Radar Waveforms","authors":"Matthew B. Heintzelman;Daniel B. Herr;Charles A. Mohr;Shannon D. Blunt;Cenk Sahin;Andrew Kordik","doi":"10.1109/TRS.2025.3564236","DOIUrl":null,"url":null,"abstract":"This work seeks to elucidate the relationship between interfering frequency-modulated (FM) radar waveforms and their observed separability. A statistical and analytical framework is developed through which the average separability is determined as a function of the mutual time–bandwidth product between the interfering waveforms. The analytically derived predictor for waveform separability is then compared to a long-observed heuristic. Since random waveforms exhibit stochastic cross correlations, the maximum deviation above the analytically derived predictor is also examined. High-dimensional Monte Carlo simulations are used to numerically validate the analytical results.","PeriodicalId":100645,"journal":{"name":"IEEE Transactions on Radar Systems","volume":"3 ","pages":"768-788"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Radar Systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10976448/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This work seeks to elucidate the relationship between interfering frequency-modulated (FM) radar waveforms and their observed separability. A statistical and analytical framework is developed through which the average separability is determined as a function of the mutual time–bandwidth product between the interfering waveforms. The analytically derived predictor for waveform separability is then compared to a long-observed heuristic. Since random waveforms exhibit stochastic cross correlations, the maximum deviation above the analytically derived predictor is also examined. High-dimensional Monte Carlo simulations are used to numerically validate the analytical results.