{"title":"基于符号雷达脉冲序列分析的PRI调制识别启发式方法","authors":"Yu-Shan Liang, You-Gang Chen, Teresa Bei-Yi Shen","doi":"10.1109/ECICE55674.2022.10042927","DOIUrl":null,"url":null,"abstract":"We present a novel heuristic approach for pulse repetition interval (PRI) modulation recognition by identifying the temporal pattern based on a symbolic radar pulse train analysis. The analysis of the symbolization of radar pulse trains is presented as a metric for the ability to identify the temporal PRI modulation characteristic. The recognition approach developed based on a time series analysis technique has to transform the radar pulse trains into a corresponding sequence of symbols. We retain temporal information from transforming the time series of pulse trains through numerical computations. The PRI pattern is obtained for real-time monitoring, and then the modulation types are identified based on characteristics. The simulation results show that the proposed algorithm can effectively recognize the PRI modulation type of radar pulse trains.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Heuristic Approach for PRI Modulation Recognition Based on Symbolic Radar Pulse Trains Analysis\",\"authors\":\"Yu-Shan Liang, You-Gang Chen, Teresa Bei-Yi Shen\",\"doi\":\"10.1109/ECICE55674.2022.10042927\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a novel heuristic approach for pulse repetition interval (PRI) modulation recognition by identifying the temporal pattern based on a symbolic radar pulse train analysis. The analysis of the symbolization of radar pulse trains is presented as a metric for the ability to identify the temporal PRI modulation characteristic. The recognition approach developed based on a time series analysis technique has to transform the radar pulse trains into a corresponding sequence of symbols. We retain temporal information from transforming the time series of pulse trains through numerical computations. The PRI pattern is obtained for real-time monitoring, and then the modulation types are identified based on characteristics. The simulation results show that the proposed algorithm can effectively recognize the PRI modulation type of radar pulse trains.\",\"PeriodicalId\":282635,\"journal\":{\"name\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECICE55674.2022.10042927\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECICE55674.2022.10042927","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Heuristic Approach for PRI Modulation Recognition Based on Symbolic Radar Pulse Trains Analysis
We present a novel heuristic approach for pulse repetition interval (PRI) modulation recognition by identifying the temporal pattern based on a symbolic radar pulse train analysis. The analysis of the symbolization of radar pulse trains is presented as a metric for the ability to identify the temporal PRI modulation characteristic. The recognition approach developed based on a time series analysis technique has to transform the radar pulse trains into a corresponding sequence of symbols. We retain temporal information from transforming the time series of pulse trains through numerical computations. The PRI pattern is obtained for real-time monitoring, and then the modulation types are identified based on characteristics. The simulation results show that the proposed algorithm can effectively recognize the PRI modulation type of radar pulse trains.
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