{"title":"A nonparametric IR-UWB TOA estimator based on conditional tests","authors":"Yanlong Zhang, F. Sun, Weidong Chen","doi":"10.1109/ICUWB.2012.6340431","DOIUrl":null,"url":null,"abstract":"In this paper, a nonparametric approach for time-of-arrival (TOA) estimation in impulse radio ultra wide band (IR-UWB) signals is proposed. It exploits the idea of nonparametric detection, which is always utilized in radar systems for detecting targets in a background of noise with unknown statistical properties. The proposed nonparametric TOA estimator is obtained by basing a well-known generalized sign detector upon conditional statistical test with only a symmetry distribution assumption on the noise probability density functions. The main advantage of nonparametric estimators for ultra wide band signals is that they can be implemented by high sampling rate low resolution ADCs or fast comparator, instead of high sampling rate high resolution ADCs which are too complicated and power-hungry to implement. The effectiveness of our nonparametric detection-based estimator is demonstrated by comparing with energy-detection (ED) estimators via simulation.","PeriodicalId":260071,"journal":{"name":"2012 IEEE International Conference on Ultra-Wideband","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Ultra-Wideband","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICUWB.2012.6340431","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
In this paper, a nonparametric approach for time-of-arrival (TOA) estimation in impulse radio ultra wide band (IR-UWB) signals is proposed. It exploits the idea of nonparametric detection, which is always utilized in radar systems for detecting targets in a background of noise with unknown statistical properties. The proposed nonparametric TOA estimator is obtained by basing a well-known generalized sign detector upon conditional statistical test with only a symmetry distribution assumption on the noise probability density functions. The main advantage of nonparametric estimators for ultra wide band signals is that they can be implemented by high sampling rate low resolution ADCs or fast comparator, instead of high sampling rate high resolution ADCs which are too complicated and power-hungry to implement. The effectiveness of our nonparametric detection-based estimator is demonstrated by comparing with energy-detection (ED) estimators via simulation.