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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Hauptverfasser: Olfati-Saber, Reza, Jalalkamali, Parisa
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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.
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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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