Bridging GPS outages of tightly-coupled GPS/SINS using GMDH neural network

A tightly-coupled GPS (global positioning system)/SINS (strap-down inertial navigation system) based on a GMDH (group method of data handling) neural network was presented to solve the problem of degraded accuracy for less than four visible GPS satellites with poor signal quality. Positions and velocities of the satellites were predicted by a GMDH neural network, and the pseudo-ranges and pseudo-range rates received by the GPS receiver were simulated to ensure the regular operation of the GPS/SINS Kalman filter during outages. In the mathematical simulation a tightly-coupled navigation system with a proposed approach has better navigation accuracy during GPS outages, and the anti-jamming ability is strengthened for the tightly-coupled navigation system.