{"title":"双频多普勒测距估计的相位展开技术","authors":"N. Hassan, S. Yusof, K. M. Yusof","doi":"10.1109/MICC.2015.7725452","DOIUrl":null,"url":null,"abstract":"The usage of phase information from multiple frequency measurement has become a common practice in many different fields especially in ranging estimation techniques. The techniques can give higher accuracy and its can cover a long-range application compared to the conventional technique. However, in real situation this phase information is subjected to distortion, noise, and other vagaries that make the phase information do not carry the right information anymore. In this paper, the phase unwrapping techniques based on data association is introduced to reduce the noise effect on phase estimation. Three different phase unwrapping techniques are explored, which are Maximum Likelihood Estimation, Least Square Estimator and Chinese Remainder Theorem. The performance metric of those techniques is based on Root Mean Square Error (RMSE). The results showed, for countless data sample, a Maximum Likelihood Estimation technique is preferred. But if data sample is limited and insufficient Least Square Estimator techniques is more suitable to be used.","PeriodicalId":225244,"journal":{"name":"2015 IEEE 12th Malaysia International Conference on Communications (MICC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Phase unwrapping technique for dual-frequency Doppler ranging estimation\",\"authors\":\"N. Hassan, S. Yusof, K. M. Yusof\",\"doi\":\"10.1109/MICC.2015.7725452\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The usage of phase information from multiple frequency measurement has become a common practice in many different fields especially in ranging estimation techniques. The techniques can give higher accuracy and its can cover a long-range application compared to the conventional technique. However, in real situation this phase information is subjected to distortion, noise, and other vagaries that make the phase information do not carry the right information anymore. In this paper, the phase unwrapping techniques based on data association is introduced to reduce the noise effect on phase estimation. Three different phase unwrapping techniques are explored, which are Maximum Likelihood Estimation, Least Square Estimator and Chinese Remainder Theorem. The performance metric of those techniques is based on Root Mean Square Error (RMSE). The results showed, for countless data sample, a Maximum Likelihood Estimation technique is preferred. But if data sample is limited and insufficient Least Square Estimator techniques is more suitable to be used.\",\"PeriodicalId\":225244,\"journal\":{\"name\":\"2015 IEEE 12th Malaysia International Conference on Communications (MICC)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 12th Malaysia International Conference on Communications (MICC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MICC.2015.7725452\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 12th Malaysia International Conference on Communications (MICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MICC.2015.7725452","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Phase unwrapping technique for dual-frequency Doppler ranging estimation
The usage of phase information from multiple frequency measurement has become a common practice in many different fields especially in ranging estimation techniques. The techniques can give higher accuracy and its can cover a long-range application compared to the conventional technique. However, in real situation this phase information is subjected to distortion, noise, and other vagaries that make the phase information do not carry the right information anymore. In this paper, the phase unwrapping techniques based on data association is introduced to reduce the noise effect on phase estimation. Three different phase unwrapping techniques are explored, which are Maximum Likelihood Estimation, Least Square Estimator and Chinese Remainder Theorem. The performance metric of those techniques is based on Root Mean Square Error (RMSE). The results showed, for countless data sample, a Maximum Likelihood Estimation technique is preferred. But if data sample is limited and insufficient Least Square Estimator techniques is more suitable to be used.