Location Estimation for Multiple Targets Using Tree Search Algorithms under Cooperative Surveillance of Multiple Robots 


Vol. 38,  No. 9, pp. 782-791, Sep.  2013


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  Abstract

This paper proposes the location estimation techniques of distributed targets with the multi-sensor data perceived through IR sensors of the military robots. In order to match up targets with measured azimuths, we apply the maximum likelihood (ML), depth-first, and breadth-first tree search algorithms, in which we use the measured azimuths and the number of pixels on IR screen for pruning branches and selecting candidates. After matching up targets with azimuths, we estimate the coordinate of each target by obtaining the intersection point of the azimuths with the least square error (LSE) algorithm. The experimental results show the probability of missing target, mean of the number of calculating nodes, and mean error of the estimated coordinates of the proposed algorithms.

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  Cite this article

[IEEE Style]

S. R. Park and S. Noh, "Location Estimation for Multiple Targets Using Tree Search Algorithms under Cooperative Surveillance of Multiple Robots," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 9, pp. 782-791, 2013. DOI: .

[ACM Style]

So Ryoung Park and Sanguk Noh. 2013. Location Estimation for Multiple Targets Using Tree Search Algorithms under Cooperative Surveillance of Multiple Robots. The Journal of Korean Institute of Communications and Information Sciences, 38, 9, (2013), 782-791. DOI: .

[KICS Style]

So Ryoung Park and Sanguk Noh, "Location Estimation for Multiple Targets Using Tree Search Algorithms under Cooperative Surveillance of Multiple Robots," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 9, pp. 782-791, 9. 2013.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880