{"title":"基于窗口滑动算法的多功能雷达工作模式变化点检测","authors":"Zhi Tang, Xueqiong Li, Xucan Chen","doi":"10.1109/AINIT59027.2023.10212583","DOIUrl":null,"url":null,"abstract":"Accurately detecting the change points of work mode is crucial for identifying the behavioral intentions of multi-functional radar (MFR). However, the intercepted MFR pulse sequence is filled with various noise, generating a large amount of measurement error, spurious pulses and lost pulses, making it difficult to locate change point positions. A window-sliding change point detection (Win-CPD) algorithm is applied in this paper, which detects change points by computing the discrepancy between two adjacent windows sliding along the MFR sequence, and discovering the peak in the discrepancy curve when the two windows cover different segments. Experiment results have verified the effectiveness and superiority of this algorithm.","PeriodicalId":276778,"journal":{"name":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","volume":"165 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Change Point Detection Of Multi-functional Radar Work Mode Based On Window-sliding Algorithm\",\"authors\":\"Zhi Tang, Xueqiong Li, Xucan Chen\",\"doi\":\"10.1109/AINIT59027.2023.10212583\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Accurately detecting the change points of work mode is crucial for identifying the behavioral intentions of multi-functional radar (MFR). However, the intercepted MFR pulse sequence is filled with various noise, generating a large amount of measurement error, spurious pulses and lost pulses, making it difficult to locate change point positions. A window-sliding change point detection (Win-CPD) algorithm is applied in this paper, which detects change points by computing the discrepancy between two adjacent windows sliding along the MFR sequence, and discovering the peak in the discrepancy curve when the two windows cover different segments. Experiment results have verified the effectiveness and superiority of this algorithm.\",\"PeriodicalId\":276778,\"journal\":{\"name\":\"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)\",\"volume\":\"165 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AINIT59027.2023.10212583\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINIT59027.2023.10212583","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Change Point Detection Of Multi-functional Radar Work Mode Based On Window-sliding Algorithm
Accurately detecting the change points of work mode is crucial for identifying the behavioral intentions of multi-functional radar (MFR). However, the intercepted MFR pulse sequence is filled with various noise, generating a large amount of measurement error, spurious pulses and lost pulses, making it difficult to locate change point positions. A window-sliding change point detection (Win-CPD) algorithm is applied in this paper, which detects change points by computing the discrepancy between two adjacent windows sliding along the MFR sequence, and discovering the peak in the discrepancy curve when the two windows cover different segments. Experiment results have verified the effectiveness and superiority of this algorithm.