Collaborative target tracking using distributed Kalman filtering on mobile sensor networks
In this paper, we introduce a theoretical frame work for coupled distributed estimation and motion control of mobile sensor networks for collaborative target tracking. We use a Fisher Information theoretic metric for quality of sensed data. The mobile sensing agents seek to improve the information v...
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creator | Olfati-Saber, Reza Jalalkamali, Parisa |
description | In this paper, we introduce a theoretical frame work for coupled distributed estimation and motion control of mobile sensor networks for collaborative target tracking. We use a Fisher Information theoretic metric for quality of sensed data. The mobile sensing agents seek to improve the information value of their sensed data while maintaining a safe-distance from other neighboring agents (i.e. perform information-driven flocking). We provide a formal stability analysis of continuous Kalman-Consensus filtering (KCF) algorithm on a mobile sensor network with a flocking-based mobility control model. The discrete-time counterpart of this coupled estimation and control algorithm is successfully applied to tracking of two types of targets with stochastic linear and nonlinear dynamics. |
doi_str_mv | 10.1109/ACC.2011.5990979 |
format | Conference Proceeding |
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The discrete-time counterpart of this coupled estimation and control algorithm is successfully applied to tracking of two types of targets with stochastic linear and nonlinear dynamics.</description><subject>Algorithm design and analysis</subject><subject>collaborative localization</subject><subject>distributed Kalman filtering</subject><subject>Estimation</subject><subject>Heuristic algorithms</subject><subject>information-driven control</subject><subject>Mobile communication</subject><subject>Mobile computing</subject><subject>mobile sensor networks</subject><subject>Sensors</subject><subject>Target tracking</subject><issn>0743-1619</issn><issn>2378-5861</issn><isbn>1457700808</isbn><isbn>9781457700804</isbn><isbn>9781457700798</isbn><isbn>1457700816</isbn><isbn>9781457700811</isbn><isbn>1457700794</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkL1OwzAYRc2fRFu6I7H4BVL82Y5_xiqigKjEAgtLZSefK9M0QbYL4u1RRZdzhyPd4RByC2wBwOz9smkWnAEsamuZ1faMzK02IGutGdPWnJMJF9pUtVFwQaYnYZi5JBOmpahAgb0m05w_GQNrFZuQj2bse-fH5Er8Rlpc2mKhJbl2F4ctPeQju5hLiv5QsKMvrt-7gYbYF0xHOQ50P_rYI8045DHRAcvPmHb5hlwF12ecn3ZG3lcPb81TtX59fG6W6ypyCaXitevqgJ30njnFIDgmuPRBthqFFDKElisjFQjRcuFCLQwHFRR2tXdWezEjd_-_ERE3XynuXfrdnBqJP5LRWD8</recordid><startdate>201106</startdate><enddate>201106</enddate><creator>Olfati-Saber, Reza</creator><creator>Jalalkamali, Parisa</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201106</creationdate><title>Collaborative target tracking using distributed Kalman filtering on mobile sensor networks</title><author>Olfati-Saber, Reza ; Jalalkamali, Parisa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i241t-25ad5fed4bb0a601fa0324bf4c7e3434ffc26846133c23af538216f6ed5ba97b3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithm design and analysis</topic><topic>collaborative localization</topic><topic>distributed Kalman filtering</topic><topic>Estimation</topic><topic>Heuristic algorithms</topic><topic>information-driven control</topic><topic>Mobile communication</topic><topic>Mobile computing</topic><topic>mobile sensor networks</topic><topic>Sensors</topic><topic>Target tracking</topic><toplevel>online_resources</toplevel><creatorcontrib>Olfati-Saber, Reza</creatorcontrib><creatorcontrib>Jalalkamali, Parisa</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Olfati-Saber, Reza</au><au>Jalalkamali, Parisa</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Collaborative target tracking using distributed Kalman filtering on mobile sensor networks</atitle><btitle>Proceedings of the 2011 American Control Conference</btitle><stitle>ACC</stitle><date>2011-06</date><risdate>2011</risdate><spage>1100</spage><epage>1105</epage><pages>1100-1105</pages><issn>0743-1619</issn><eissn>2378-5861</eissn><isbn>1457700808</isbn><isbn>9781457700804</isbn><eisbn>9781457700798</eisbn><eisbn>1457700816</eisbn><eisbn>9781457700811</eisbn><eisbn>1457700794</eisbn><abstract>In this paper, we introduce a theoretical frame work for coupled distributed estimation and motion control of mobile sensor networks for collaborative target tracking. We use a Fisher Information theoretic metric for quality of sensed data. The mobile sensing agents seek to improve the information value of their sensed data while maintaining a safe-distance from other neighboring agents (i.e. perform information-driven flocking). We provide a formal stability analysis of continuous Kalman-Consensus filtering (KCF) algorithm on a mobile sensor network with a flocking-based mobility control model. The discrete-time counterpart of this coupled estimation and control algorithm is successfully applied to tracking of two types of targets with stochastic linear and nonlinear dynamics.</abstract><pub>IEEE</pub><doi>10.1109/ACC.2011.5990979</doi><tpages>6</tpages></addata></record> |
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subjects | Algorithm design and analysis collaborative localization distributed Kalman filtering Estimation Heuristic algorithms information-driven control Mobile communication Mobile computing mobile sensor networks Sensors Target tracking |
title | Collaborative target tracking using distributed Kalman filtering on mobile sensor networks |
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