Performance enhancement of low-cost, high-accuracy, state estimation for vehicle collision prevention system using ANFIS

In this paper, a low-cost navigation system that fuses the measurements of the inertial navigation system (INS) and the global positioning system (GPS) receiver is developed. First, the system's dynamics are obtained based on a vehicle's kinematic model. Second, the INS and GPS measurements are fused using an extended Kalman filter (EKF) approach. Subsequently, an artificial intelligence based approach for the fusion of INS/GPS measurements is developed based on an Input-Delayed Adaptive Neuro-Fuzzy Inference System (IDANFIS). Experimental tests are conducted to demonstrate the performance of the two sensor fusion approaches. It is found that the use of the proposed IDANFIS approach achieves a reduction in the integration development time and an improvement in the estimation accuracy of the vehicle's position and velocity compared to the EKF based approach. (C) 2013 Elsevier Ltd. All rights reserved.