{"title":"智能管理多个传感器,增强态势感知能力","authors":"Eric D. Nelson, J. Irvine","doi":"10.1109/AIPR.2010.5759715","DOIUrl":null,"url":null,"abstract":"Wide area motion imagery (WAMI) offers the promise of persistent surveillance over large regions. However, the combination of lower frame rate and coarser spatial resolution found in most WAMI systems can limit the ability to track multiple targets. One way to address this limitation is to employ the wide-area sensor in concert with one or more high resolution sensors. We have developed a capability called Sensor Management for Adaptive Reconnaissance and Tracking (SMART), for tasking an arbitrary number of high-fidelity assets, working with the WAMI sensor to maximize situational awareness based on a prevailing set of conditions and target priorities. We present a simulation framework for exploring performance of various sensor management strategies and present the findings from an initial set of experiments.","PeriodicalId":128378,"journal":{"name":"2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)","volume":"66 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Intelligent management of multiple sensors for enhanced situational awareness\",\"authors\":\"Eric D. Nelson, J. Irvine\",\"doi\":\"10.1109/AIPR.2010.5759715\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wide area motion imagery (WAMI) offers the promise of persistent surveillance over large regions. However, the combination of lower frame rate and coarser spatial resolution found in most WAMI systems can limit the ability to track multiple targets. One way to address this limitation is to employ the wide-area sensor in concert with one or more high resolution sensors. We have developed a capability called Sensor Management for Adaptive Reconnaissance and Tracking (SMART), for tasking an arbitrary number of high-fidelity assets, working with the WAMI sensor to maximize situational awareness based on a prevailing set of conditions and target priorities. We present a simulation framework for exploring performance of various sensor management strategies and present the findings from an initial set of experiments.\",\"PeriodicalId\":128378,\"journal\":{\"name\":\"2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)\",\"volume\":\"66 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIPR.2010.5759715\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2010.5759715","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent management of multiple sensors for enhanced situational awareness
Wide area motion imagery (WAMI) offers the promise of persistent surveillance over large regions. However, the combination of lower frame rate and coarser spatial resolution found in most WAMI systems can limit the ability to track multiple targets. One way to address this limitation is to employ the wide-area sensor in concert with one or more high resolution sensors. We have developed a capability called Sensor Management for Adaptive Reconnaissance and Tracking (SMART), for tasking an arbitrary number of high-fidelity assets, working with the WAMI sensor to maximize situational awareness based on a prevailing set of conditions and target priorities. We present a simulation framework for exploring performance of various sensor management strategies and present the findings from an initial set of experiments.