一种改进的地形熵匹配导航算法

提出了一种改进的地形熵辅助导航算法.因为地形熵算法丢掉了地形的相对位置信息及对地形数据做了归一化处理,使得其在地形跟随/地形回避中的应用存在着匹配误差容易发散的问题.基于此点,提出了基于卡尔曼滤波的惯性地形辅助导航方法,交互信息量等方法的地形熵算法,以改进该算法在地形跟随/地形回避中应用的性能.最后用matlab软件根据分形学中Weierstrass-Mandelbrot函数产生了模拟的数字地图,并对该地形匹配导航方法作了仿真研究,仿真结果表明该方法可以抑制误差的发散,并提高了地形匹配的定位精度.

A Modified Terrain - entropy Matching Algorithm

The paper introduces an improved terrain-entropy navigation algorithm. The primary bug of this algorithm is that it discards the relative position information of terrain data and the normalized processing. Based on this, a sandia inertial terrain aided navigation method for Kalman filter is offered and the maximization of mutual information is synthesized, the performance of terrain-entropy algorithm is improved. Lastly the simulated digital maps are produced by computer on topography of Weierstrass-Mandelbrot function on matlab for simulation. Better results are obtained by simulation.