{"title":"基于雷达时频谱的静止目标概率模型","authors":"Heemang Song, Hyun-Chool Shin","doi":"10.1109/ICOIN.2018.8343240","DOIUrl":null,"url":null,"abstract":"In this paper, we suggest a probability model of stationary object for classifying the stationary and moving objects using radar time-frequency spectrum. In radar spectrum, the stationary object has a slope that matches the velocity of ego vehicle. Applying the Hough transform, the slope is estimated and converts to velocity. The difference between the velocity of ego vehicle and estimated velocity is used to compare characteristic of the stationary and moving objects. We experimentally compare characteristic of the objects and suggest a probability model of stationary object using exponential distribution.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A probability model of stationary object using radar time-frequency spectrum\",\"authors\":\"Heemang Song, Hyun-Chool Shin\",\"doi\":\"10.1109/ICOIN.2018.8343240\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we suggest a probability model of stationary object for classifying the stationary and moving objects using radar time-frequency spectrum. In radar spectrum, the stationary object has a slope that matches the velocity of ego vehicle. Applying the Hough transform, the slope is estimated and converts to velocity. The difference between the velocity of ego vehicle and estimated velocity is used to compare characteristic of the stationary and moving objects. We experimentally compare characteristic of the objects and suggest a probability model of stationary object using exponential distribution.\",\"PeriodicalId\":228799,\"journal\":{\"name\":\"2018 International Conference on Information Networking (ICOIN)\",\"volume\":\"141 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Information Networking (ICOIN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOIN.2018.8343240\",\"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 International Conference on Information Networking (ICOIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOIN.2018.8343240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A probability model of stationary object using radar time-frequency spectrum
In this paper, we suggest a probability model of stationary object for classifying the stationary and moving objects using radar time-frequency spectrum. In radar spectrum, the stationary object has a slope that matches the velocity of ego vehicle. Applying the Hough transform, the slope is estimated and converts to velocity. The difference between the velocity of ego vehicle and estimated velocity is used to compare characteristic of the stationary and moving objects. We experimentally compare characteristic of the objects and suggest a probability model of stationary object using exponential distribution.
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