Localization Algorithm based on Positive Semi-definite Programming in Wireless Sensor Networks

Provided by: Science & Engineering Research Support soCiety (SERSC)
Topic: Mobility
Format: PDF
In this paper, the authors propose an algorithm to locate an object with unknown coordinates based on the positive semi-definite programming in the wireless sensor networks, assuming that the squared error of the measured distance follows Gaussian distribution. They first obtain the estimator of the object location based on the maximum likelihood criterion; then considering that the estimator is a non-convex function with respect to the measured distances between the object and the anchors with known coordinates, they transform the non-convex optimization to convex one by the positive semi-definite relaxation; and finally, they take the optimal solution of the convex optimization as the estimated value of the object location.

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