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Proceedings Paper

Sequential detection of targets in distributed systems
Author(s): Alexander G. Tartakovsky; X. Rong Li; George Yaralov
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Paper Abstract

It is supposed that there is a multisensor system in which each sensor performs sequential detection of a target. Then the binary decisions on target presence and absence are transmitted to a fusion center, which combines them to improve the performance of the system. We assume that sensors represent multichannel systems with possibly each one having different number of channels. Sequential detection of a target in each sensor is done by implementing a generalized Wald's sequential probability ratio test which is based on the maximum likelihood ratio statistic and allows one to fix the false alarm rate and the mis-detection rate at specified levels. We first show that this sequential detection procedure is asymptotically optimal for general statistical models in the sense of minimizing the expected sample size when the probabilities of errors vanish. We then construct the optimal non-sequential fusion rule that waits until all the local decisions in all sensors are made and then fuses them. It is optimal in the sense of maximizing the probability of target detection for a fixed probability of a false alarm or minimizing the maximal probability of error (minimax criterion). An analysis shows that the final decision can be made substantially more reliable even for a small number of sensors (3-5). The performance of the system is illustrated by the example of detecting a deterministic signal in correlated (color) Gaussian noise. In this example, we provide both the results of theoretical analysis and the results of Monte Carlo experiment. These results allow us to conclude that the use of the sequential detection algorithm substantially reduces the required resources of the system compared to the best non-sequential algorithm.

Paper Details

Date Published: 16 August 2001
PDF: 15 pages
Proc. SPIE 4380, Signal Processing, Sensor Fusion, and Target Recognition X, (16 August 2001); doi: 10.1117/12.436951
Show Author Affiliations
Alexander G. Tartakovsky, Univ. of Southern California (United States)
X. Rong Li, Univ. of New Orleans (United States)
George Yaralov, Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 4380:
Signal Processing, Sensor Fusion, and Target Recognition X
Ivan Kadar, Editor(s)

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