Adaptive code tracking loop design for GNSS receivers

In this paper, in order to improve the Global Navigation Satellite System (GNSS) code tracking performance, a novel adaptive proportional-integral-derivative (PID) controlling strategy based on Radial Basis Function (RBF) neural network (NN) online identification is proposed in the loop filter design of the code tracking loop for a GNSS receiver. This proposed technique combines conventional PID controlling strategy with neural network algorithm, and generates a new type of PID controller with robustness and adaptability. Due to the self-learning ability of neural network, this proposed technique can self tune and automatically modify the robust PID parameters online by using gradient descent method. In order to illustrate the effectiveness and robustness of the proposed adaptive code tracking technique for GNSS receivers, simulation campaigns have been performed on the Galileo E1 Open Service (OS) BOC(1,1) signals. The simulation results show that this proposed code tracking technique provides adaptability, strong robustness and satisfactory performance, which satisfies stringent performance requirements for the code tracking process when the GNSS receiver works in nonlinear and time-varying signal environments.