{"title":"An Identification Algorithm of Passive Millimeter Wave Detection Armored Targets Based on Signal Complexity","authors":"J. Feng, Xiaomin Zhang","doi":"10.12733/JICS20105676","DOIUrl":null,"url":null,"abstract":"In the past, there had been a higher error recognition rate when using passive millimeter wave technology identifled armored targets. In order to solve this problem, proposed a recognition method for armored targets based on signal complexity. Started from the passive millimeter wave radiation mechanism of armored targets, presented a concept, which named as signal complexity, analyzed the signal complexity of armored targets, and got its’ recognition algorithm. Simulation results show that it not only ensures the correct recognition rate of armored targets, but also greatly reduces the probability of mistakenly identifled the interference target (such as planer metal and ground water) as an armored target.","PeriodicalId":213716,"journal":{"name":"The Journal of Information and Computational Science","volume":"969 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Information and Computational Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12733/JICS20105676","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In the past, there had been a higher error recognition rate when using passive millimeter wave technology identifled armored targets. In order to solve this problem, proposed a recognition method for armored targets based on signal complexity. Started from the passive millimeter wave radiation mechanism of armored targets, presented a concept, which named as signal complexity, analyzed the signal complexity of armored targets, and got its’ recognition algorithm. Simulation results show that it not only ensures the correct recognition rate of armored targets, but also greatly reduces the probability of mistakenly identifled the interference target (such as planer metal and ground water) as an armored target.