tailieunhanh - Báo cáo hóa học: " Nonmyopic Sensor Scheduling and its Efficient Implementation for Target Tracking Applications"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Nonmyopic Sensor Scheduling and its Efficient Implementation for Target Tracking Applications | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 31520 Pages 1-18 DOI ASP 2006 31520 Nonmyopic Sensor Scheduling and its Efficient Implementation for Target Tracking Applications Amit S. Chhetri 1 Darryl Morrell 1 2 and Antonia Papandreou-Suppappola1 1 Department of Electrical Engineering Arizona State University Tempe AZ 85287 USA 2 Department of Engineering Arizona State University Tempe AZ 85287 USA Received 12 May 2005 Revised 1 October 2005 Accepted 8 November 2005 Recommended for Publication by Joe C. Chen We propose two nonmyopic sensor scheduling algorithms for target tracking applications. We consider a scenario where a bearing-only sensor is constrained to move in a finite number of directions to track a target in a two-dimensional plane. Both algorithms provide the best sensor sequence by minimizing a predicted expected scheduler cost over a finite time-horizon. The first algorithm approximately computes the scheduler costs based on the predicted covariance matrix of the tracker error. The second algorithm uses the unscented transform in conjunction with a particle filter to approximate covariance-based costs or information-theoretic costs. We also propose the use of two branch-and-bound-based optimal pruning algorithms for efficient implementation of the scheduling algorithms. We design the first pruning algorithm by combining branch-and-bound with a breadth-first search and a greedy-search the second pruning algorithm combines branch-and-bound with a uniform-cost search. Simulation results demonstrate the advantage of nonmyopic scheduling over myopic scheduling and the significant savings in computational and memory resources when using the pruning algorithms. Copyright 2006 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION In recent years advances in sensor technology coupled with embedded systems and wireless networking has made it possible to deploy sensors in numerous .

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