Study of Comparing Several Nonlinear Filtering Algorithms in Carrier-based Aircraft Positioning

Abstract

In order to improve the positioning accuracy of the landing guidance radar to the carrier aircraft, the nonlinear filtering algorithm is used to estimate the positioning of the carrier aircraft. The main algorithms of nonlinear filtering, such as extended Kalman filter, unscented Kalman filter and particle filter, are analyzed and compared. A typical nonlinear model is simulated to verify the performance of these algorithms. The simulation results show that the estimation accuracy of the particle filter algorithm is better than the other two filter algorithms.