Abstract:In BDS/GPS combination positioning, it is a very important step to select the satellite combination with the best spatial location. The traditional satellite selection algorithm involves a large number of matrix multiplication and inversion operations, so the calculation is large and the real-time is low. For the problem of rapidly fixing position, the authors, considering the positioning accuracy and real-time requirements, propose a new satellite selection algorithm, which combines the BP neural network and genetic algorithm, and uses the geometric dilution of precision (GDOP) as the basis of judging positioning accuracy. Through the comparison of GDOP and the running time acquired by this algorithm and the method of minimum geometric dilution of precision, it is found that the proposed algorithm can greatly reduce the computational complexity and ensure the positioning accuracy, thus exhibiting good real-time and feasibility.
张兆龙, 王跃钢, 腾红磊, 王乐. 一种基于遗传算法和BP神经网络的选星方法[J]. 物探与化探, 2017, 41(5): 946-950.
ZHANG Zhao-Long, WANG Yue-Gang, TENG Hong-Lei, WANG Le. A satellite selection algorithm based on genetic algorithm and BP neural network. Geophysical and Geochemical Exploration, 2017, 41(5): 946-950.