{"title":"一种新的跳频信号参数估计方法","authors":"Yibing Li, Xiaochen Guo, Fei Yu, Qian Sun","doi":"10.1109/USNC-URSI.2018.8602599","DOIUrl":null,"url":null,"abstract":"A parameter estimation algorithm for multiple frequency-hopping (FH) signals based on maximum energy difference is proposed in this paper. First, the time-frequency (TF) matrix is obtained by TF analysis such as short-time Fourier transform (STFT) and smoothed pseudo wigner-ville distribution (SPWVD). Then, the carrier frequency and the TF data with valid frequency are determined according to the distribution of energy. Next, the number of signal segments and window length in each nonzero row of the TF data is obtained. Finally, hopping time and hop cycle are estimated based on the maximum energy difference. Simulation results indicate that the proposed algorithm has better anti-noise performance than the TF pattern modification method and the STFT-SPWVD method. The new method is suitable for asynchronous and synchronous network.","PeriodicalId":203781,"journal":{"name":"2018 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"55 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Parameter Estimation Method for Frequency Hopping Signals\",\"authors\":\"Yibing Li, Xiaochen Guo, Fei Yu, Qian Sun\",\"doi\":\"10.1109/USNC-URSI.2018.8602599\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A parameter estimation algorithm for multiple frequency-hopping (FH) signals based on maximum energy difference is proposed in this paper. First, the time-frequency (TF) matrix is obtained by TF analysis such as short-time Fourier transform (STFT) and smoothed pseudo wigner-ville distribution (SPWVD). Then, the carrier frequency and the TF data with valid frequency are determined according to the distribution of energy. Next, the number of signal segments and window length in each nonzero row of the TF data is obtained. Finally, hopping time and hop cycle are estimated based on the maximum energy difference. Simulation results indicate that the proposed algorithm has better anti-noise performance than the TF pattern modification method and the STFT-SPWVD method. The new method is suitable for asynchronous and synchronous network.\",\"PeriodicalId\":203781,\"journal\":{\"name\":\"2018 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)\",\"volume\":\"55 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/USNC-URSI.2018.8602599\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/USNC-URSI.2018.8602599","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Parameter Estimation Method for Frequency Hopping Signals
A parameter estimation algorithm for multiple frequency-hopping (FH) signals based on maximum energy difference is proposed in this paper. First, the time-frequency (TF) matrix is obtained by TF analysis such as short-time Fourier transform (STFT) and smoothed pseudo wigner-ville distribution (SPWVD). Then, the carrier frequency and the TF data with valid frequency are determined according to the distribution of energy. Next, the number of signal segments and window length in each nonzero row of the TF data is obtained. Finally, hopping time and hop cycle are estimated based on the maximum energy difference. Simulation results indicate that the proposed algorithm has better anti-noise performance than the TF pattern modification method and the STFT-SPWVD method. The new method is suitable for asynchronous and synchronous network.
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