Simulated Annealing Clustering for Optimum GPS Satellite Selection
M. Ranjbar, Mohammad Reza Mosavi · 2012
This paper utilizes a clustering approach based on Simulated Annealing (SA) method to select optimum satellite subsets from the visible satellites. Geometric Dilution of Precision (GDOP) is used as criteria of optimality. The lower the values of the GDOP number, the better the geometric strength, and vice versa. Not needing to calculate the inverse matrix, which is time-consuming process, is a dramatically important advantage of using this method, so a great reduction in computational cost is achieved. SA is a powerful technique to obtain a close approximation to the global optimum for a given problem. The evaluation of the performance of the proposed method is done by validation measures. The external validation measures, entropy and purity, are used to measure the extent to which cluster labels affirm with the externally given class labels. The overall purity and entropy is 0.9015 and 0.3993, respectively which is an excellent result.