An efficient method for optimum selection of GPS satellites set using Recurrent Neural Network

In this paper, the neural network (NN)-based satellite geometry approximation for good or acceptable navigation satellite subset selection is presented. The approach is based on approximating the satellite geometry dilution of precision (GDOP) factors utilizing the recurrent neural network (RNN) approach. Without matrix inversion required, the NN-based approach is capable of evaluating all subsets of satellites and hence reduces the computational burden. This would enable the use of a high-integrity navigation solution without the delay required for many matrix inversions. The method employed here is applicable regardless of the number of satellite signals begin processed by the receiver.