Terrain aided navigation based on Gaussian mixture unscented particle filter
Wang De-sheng · Journal of Chinese Inertial Technology · 2011
Terrain aided navigation technology uses terrain high information to estimate the aircraft position.Since the terrain height variations are nonlinear,the terrain aided navigation uses non-linear and non-Gaussian Bayesian posterior probability estimation in essential.Particle filter has been widely studied and applied in the field of terrain aided navigation,but the particle degeneracy of particle filter will affect the positioning accuracy.In this paper,Gaussian mixed unscented particle filter(GMUPF) is used in the terrain aided navigation algorithm because of the particle degeneracy of particle filter.In the algorithm,Gaussian mixture model(GMM) is used to approximate the particles distribution,and the unscented Kalman filter is used to estimate the important density function,thus resampling is not needed.The algorithm is simulated under real terrain data,and the result shows that the GMUPF can give more accurate estimation though using less particles.