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Navigation systems based on multiple bearing measurements

机译：基于多个方位测量的导航系统

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摘要

This paper presents two navigation filters based on multiple bearing measurements. In the first, the state is augmented and an equivalent linear system is derived, while in the second the output of the system is modified in such a way that the resulting system is linear. In both cases, the design of a filtering solution relies on linear systems theory, in spite of the nonlinear nature of the system, and the resulting error dynamics can be made globally exponentially stable by applying, for example, Kalman filters. The continuous/discrete nature of the different measurement sources is taken into account, with the updates occurring in discrete time, while open-loop propagation is carried out between bearing measurements. Simulation results are presented, including Monte Carlo runs and a comparison with both the extended Kalman filter and the Bayesian Cramér-Rao bound, to assess the performance of the proposed solutions.
机译：本文介绍了基于多个方位测量的两个导航过滤器。在第一种方法中，状态被增强并且得出了一个等效的线性系统，而在第二种方法中，系统的输出被修改为使得所得的系统是线性的。在这两种情况下，尽管系统具有非线性特性，但滤波解决方案的设计仍依赖于线性系统理论，并且可以通过应用例如卡尔曼滤波器使所得误差动态全局指数稳定。考虑到不同测量源的连续/离散特性，其中更新以离散时间发生，而开环传播则在轴承测量之间进行。给出了仿真结果，包括蒙特卡罗运行以及与扩展卡尔曼滤波器和贝叶斯Cramér-Rao界的比较，以评估所提出解决方案的性能。

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