{"title":"基于因子分析的样本缺失信号重构算法","authors":"Anjun Chen, Baoshuai Wang, Jiacheng Wu","doi":"10.1117/12.2655369","DOIUrl":null,"url":null,"abstract":"The micro-Doppler modulation feature in radar echo can reflect the geometric structure and motion characteristics of targets, and is widely used in target parameter extraction and pattern recognition. Aiming at the problem of low micro-Doppler resolution under the condition of short dwell time, a sample missing signal reconstruction algorithm based on factor analysis (FA) model is proposed. Firstly, FA is used to describe the unknown complete signal, and then the mathematical model between the sample missing observation signal and the unknown complete signal is established. Then Bayesian theory is used to transform it into a full probability model. The model is solved by variable Bayesian expectation maximization (VBEM), so as to obtain the reconstruction of the complete signal. At the same time, for the problem of determining the number of FA factors, the automatic correlation determination (ARD) prior is introduced into the model to realize the automatic determination of the number of factors. Experimental results based on measured data show that the proposed method can achieve better reconstruction performance than the traditional compressive sensing (CS) method.","PeriodicalId":105577,"journal":{"name":"International Conference on Signal Processing and Communication Security","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reconstruction algorithm of sample missing signal based on factor analysis\",\"authors\":\"Anjun Chen, Baoshuai Wang, Jiacheng Wu\",\"doi\":\"10.1117/12.2655369\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The micro-Doppler modulation feature in radar echo can reflect the geometric structure and motion characteristics of targets, and is widely used in target parameter extraction and pattern recognition. Aiming at the problem of low micro-Doppler resolution under the condition of short dwell time, a sample missing signal reconstruction algorithm based on factor analysis (FA) model is proposed. Firstly, FA is used to describe the unknown complete signal, and then the mathematical model between the sample missing observation signal and the unknown complete signal is established. Then Bayesian theory is used to transform it into a full probability model. The model is solved by variable Bayesian expectation maximization (VBEM), so as to obtain the reconstruction of the complete signal. At the same time, for the problem of determining the number of FA factors, the automatic correlation determination (ARD) prior is introduced into the model to realize the automatic determination of the number of factors. Experimental results based on measured data show that the proposed method can achieve better reconstruction performance than the traditional compressive sensing (CS) method.\",\"PeriodicalId\":105577,\"journal\":{\"name\":\"International Conference on Signal Processing and Communication Security\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Signal Processing and Communication Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2655369\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Signal Processing and Communication Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2655369","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reconstruction algorithm of sample missing signal based on factor analysis
The micro-Doppler modulation feature in radar echo can reflect the geometric structure and motion characteristics of targets, and is widely used in target parameter extraction and pattern recognition. Aiming at the problem of low micro-Doppler resolution under the condition of short dwell time, a sample missing signal reconstruction algorithm based on factor analysis (FA) model is proposed. Firstly, FA is used to describe the unknown complete signal, and then the mathematical model between the sample missing observation signal and the unknown complete signal is established. Then Bayesian theory is used to transform it into a full probability model. The model is solved by variable Bayesian expectation maximization (VBEM), so as to obtain the reconstruction of the complete signal. At the same time, for the problem of determining the number of FA factors, the automatic correlation determination (ARD) prior is introduced into the model to realize the automatic determination of the number of factors. Experimental results based on measured data show that the proposed method can achieve better reconstruction performance than the traditional compressive sensing (CS) method.