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地形辅助导航是一种利用地形高度信息定位的导航技术,由于地形高度起伏是非线性的,因此地形辅助导航本质是非线性、非高斯贝叶斯后验概率估计问题。粒子滤波因为适合非线性、非高斯估计问题,被引入地形辅助导航领域得到广泛研究和应用,但粒子滤波算法存在粒子匮乏的问题,会影响定位精度。针对此问题,将高斯混合无迹粒子滤波(GMUPF)用于地形辅助导航,该算法用高斯混合模型(GMM)近似粒子分布,用无迹卡尔曼滤波(UKF)估计重要密度函数,不需要做重采样。通过用实际地形数据做飞行仿真实验,结果显示相比粒子滤波,不仅没有粒子匮乏问题,而且所用粒子数更少时估计精度略好。
Terrain Aided Navigation is a kind of navigation technology which uses the height of terrain information to locate. Since terrain height undulation is non-linear, the nature of terrain aided navigation is non-linear, non-Gaussian Bayesian posterior probability estimation problem. Particle filter is widely used in the field of terrain-assisted navigation because it is suitable for non-linear and non-Gaussian estimation problems. However, particle filter has the problem of particle shortage and affects the positioning accuracy. In order to solve this problem, GMUPF is used for terrain-aided navigation. The algorithm approximates the particle distribution by Gaussian mixture model (GMM), and estimates the important density function by unscented Kalman filter (UKF) Re-sampling. By using real terrain data to do flight simulation experiments, the results show that compared with particle filter, not only is there no particle shortage problem, but also the estimation accuracy is slightly better when the number of particles used is smaller.