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首页> 外文会议>Saint Petersburg International Conference on Integrated Navigation Systems; 20060529-31; Saint Petersburg(RU) >COMPARISON OF MODULAR AND CENTRAL TERRAIN REFERENCED NAVIGATION FILTERS
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COMPARISON OF MODULAR AND CENTRAL TERRAIN REFERENCED NAVIGATION FILTERS

机译：模块化和中央地形导航滤镜的比较

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摘要

The measurement equation of a terrain referenced navigation (TRN) system is non-linear because of the influence of a reference map connecting position and terrain height. It is possible to design different navigation filters that process radar altimeter measurements based on this measurement equation. The first proposed system is based on an extended Kalman, the second on a sigma-point, the third on a bootstrap, and the fourth on a modified particle filter. The first and second filter approximate the state probability density function by a Gaussian distribution, while the third and fourth filter allow a more general density estimation by particles. All four systems can be used as central navigation systems processing radar height measurements and estimating position, velocity, and attitude. Especially for both particle filters the system performance is not ideal, because Of the weak observability of the velocity and attitude states. In another situation where the TRN-system has to be separated from the central navigation a setup with a central Kalman filter and a terrain referenced navigation module with a reduced state space is proposed. Compared to the central TRN filters the overall accuracy of the modular filter is reduced due to the separation of the non-linear TRN-module and the linear central navigation. Anyhow, because of the reduction of the state space the modular particle filters can gain robustness and achieve similar accuracy than the central systems.
机译：由于连接位置和地形高度的参考地图的影响，地形参考导航（TRN）系统的测量方程是非线性的。可以设计不同的导航过​​滤器，以基于该测量方程式处理雷达高度计的测量。提出的第一个系统基于扩展的Kalman，第二个基于sigma-point，第三个基于自举，第四个基于修改的粒子滤波器。第一和第二滤波器通过高斯分布近似状态概率密度函数，而第三和第四滤波器允许通过粒子进行更一般的密度估计。所有这四个系统都可以用作中央导航系统，处理雷达高度测量并估计位置，速度和姿态。尤其对于两个粒子滤波器，由于速度和姿态状态的可观察性较弱，因此系统性能并不理想。在必须将TRN系统与中央导航分离的另一种情况下，提出了具有中央卡尔曼滤波器和地形参考导航模块且状态空间减少的设置。与中央TRN滤波器相比，模块化滤波器的整体精度由于非线性TRN模块和线性中央导航的分离而降低。无论如何，由于状态空间的减少，模块化粒子滤波器可以获得鲁棒性，并获得与中央系统相似的精度。

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