Computing budget allocation for optimization of sensor processing order in sequential multi-sensor fusion algorithms

Proceedings of the American Control Conference

Volumn 3, Issue , 2001, Pages 1841-1847

  Trailovic L ^a   Pao, L Y ^a  

^a UCB 450   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; MATRIX ALGEBRA; OPTIMIZATION; PROBABILITY DENSITY FUNCTION; STATISTICAL METHODS;

BUDGET ALLOCATION; CUMULATIVE DENSITY FUNCTION; SENSOR PROCESSING ORDER; SEQUENTIAL MULTI-SENSOR FUSION ALGORITHMS; SOFTWARE PACKAGE MATLAB;

SENSOR DATA FUSION;

EID: 0034840855     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/acc.2001.946004     Document Type: Conference Paper

References (19)

1. Tracking in a cluttered environment with probabilistic data association
2. Ordinal optimization for a class of deterministic and stochastic discrete resource allocation problems
3. A lower bound for the correct subset-selection probability and its application to discrete-event system simulations
4. A gradient approach for smartly allocating computing budget for discrete event simulation
5. Ordinal comparison of heuristic algorithms using stochastic optimization
6. Computing efforts allocation for ordinal optimization and discrete event simulation
7. Detection thresholds for tracking in clutter - A connection between estimation and signal processing
8. Sonar tracking of multiple targets using joint probabilistic data association
9. Alternatives to Monte-Carlo simulation evaluations of two multisensor fusion algorithms
10. On selecting a subset containing the population with the smallest variance
11. An explanation of ordinal optimization: Soft computing for hard problems
12. Ordinal optimisation and simulation
13. Universal alignment probabilities and subset selection for ordinal optimization
14. Centralized multi-sensor fusion algorithms for tracking applications
15. Optimal order of processing sensor information in sequential multisensor fusion algorithms