{"title":"未知跳频信号距离差和距离速率差的相干估计","authors":"Zhixin Liu, D. Hu, Yongjun Zhao, Yongsheng Zhao, Rui Wang, Hongzhi Jiang","doi":"10.1109/WCSP.2019.8928028","DOIUrl":null,"url":null,"abstract":"This paper addresses the estimation problem of range difference and range rate difference for unknown frequency hopping signals in passive emitter localization, considering the range migration (RM) of the high-speed moving target within the observation time. A coherent estimation algorithm based on the scaled Fourier transform is proposed. This method can effectively remove the RM and random phase effects. The whole estimation process can be fast implemented without any searching operation. Numerical experiments demonstrate that the estimation performance of proposed algorithm is superior to existing algorithms, and comparable to the maximum likelihood estimator.","PeriodicalId":108635,"journal":{"name":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Coherent Estimation of Range Difference and Range Rate Difference for Unknown Frequency Hopping Signals\",\"authors\":\"Zhixin Liu, D. Hu, Yongjun Zhao, Yongsheng Zhao, Rui Wang, Hongzhi Jiang\",\"doi\":\"10.1109/WCSP.2019.8928028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses the estimation problem of range difference and range rate difference for unknown frequency hopping signals in passive emitter localization, considering the range migration (RM) of the high-speed moving target within the observation time. A coherent estimation algorithm based on the scaled Fourier transform is proposed. This method can effectively remove the RM and random phase effects. The whole estimation process can be fast implemented without any searching operation. Numerical experiments demonstrate that the estimation performance of proposed algorithm is superior to existing algorithms, and comparable to the maximum likelihood estimator.\",\"PeriodicalId\":108635,\"journal\":{\"name\":\"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCSP.2019.8928028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCSP.2019.8928028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Coherent Estimation of Range Difference and Range Rate Difference for Unknown Frequency Hopping Signals
This paper addresses the estimation problem of range difference and range rate difference for unknown frequency hopping signals in passive emitter localization, considering the range migration (RM) of the high-speed moving target within the observation time. A coherent estimation algorithm based on the scaled Fourier transform is proposed. This method can effectively remove the RM and random phase effects. The whole estimation process can be fast implemented without any searching operation. Numerical experiments demonstrate that the estimation performance of proposed algorithm is superior to existing algorithms, and comparable to the maximum likelihood estimator.