Title | ||
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Nonmyopic sensor scheduling and its efficient implementation for target tracking applications |
Abstract | ||
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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. |
Year | DOI | Venue |
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2006 | 10.1155/ASP/2006/31520 | EURASIP J. Adv. Sig. Proc. |
Keywords | Field | DocType |
branch-and-bound-based optimal pruning algorithm,scheduler cost,scheduling algorithm,efficient implementation,nonmyopic sensor scheduling,pruning algorithm,nonmyopic sensor scheduling algorithm,sensor sequence,breadth-first search,bearing-only sensor,nonmyopic scheduling,myopic scheduling | Information theory,Mathematical optimization,Finite set,Scheduling (computing),Computer science,Particle filter,Algorithm,Unscented transform,Covariance matrix,Pruning,Covariance | Journal |
Volume | Issue | ISSN |
2006, | 1 | 1687-6180 |
Citations | PageRank | References |
15 | 1.38 | 11 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Amit S. Chhetri | 1 | 23 | 2.59 |
Darryl Morrell | 2 | 159 | 17.45 |
Antonia Papandreou-Suppappola | 3 | 234 | 29.88 |