Location Estimation for Multiple Targets Using Expanded DFS Algorithm 


Vol. 38,  No. 12, pp. 1207-1215, Dec.  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 consideration of obstacles. In order to match up targets with measured azimuths, to add to the depth-first search (DFS) algorithms in free-obstacle environment, we suggest the expanded DFS (EDS) algorithm including bypass path search, partial path search, middle level ending, and the supplementation of decision metric. 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 error rate of estimated location, mean number of calculating nodes, and mean distance between real coordinates and 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 Expanded DFS Algorithm," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 12, pp. 1207-1215, 2013. DOI: .

[ACM Style]

So Ryoung Park and Sanguk Noh. 2013. Location Estimation for Multiple Targets Using Expanded DFS Algorithm. The Journal of Korean Institute of Communications and Information Sciences, 38, 12, (2013), 1207-1215. DOI: .

[KICS Style]

So Ryoung Park and Sanguk Noh, "Location Estimation for Multiple Targets Using Expanded DFS Algorithm," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 12, pp. 1207-1215, 12. 2013.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880