On Optimal Sensor Placement and Motion Coordination for Target Tracking
CALIFORNIA UNIV SANTA BARBARA DEPT OF MECHANICAL AND ENVIRONMENTAL ENGINEERING
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This work studies optimal sensor placement and motion coordination strategies for mobile sensor networks. For a target tracking application with range sensors, we investigate the determinant of the Cramer-Rao Lower Bound and compute it in the 2D and 3D cases. We characterize the global minima of the 2D case. We propose and characterize motion coordination algorithms that steer the mobile sensor network to an optimal deployment and that are amenable to a decentralized implementation. Finally, our numerical simulations illustrate how the proposed motion coordination algorithms lead to the improved performance of an extended Kalman filter in a target tracking scenario.
- Target Direction, Range and Position Finding