An Extended Dynamic Model for Kinematic Positioning
An Extended Dynamic Model for Kinematic Positioning
复制标题
DOI：
10.1017/s0373463302002102
复制
发表时间：
2003-01
影响因子：
2.4
通讯作者：
M. Moore;Jinling Wang
中科院分区：
文献类型：
--
作者：
M. Moore;Jinling Wang
卡尔曼滤波器中动态模型面临的主要问题是当系统遇到意外的动态条件、数据采集速率的变化或系统的动态是非线性的。为了尽量减少动态建模在异常条件下产生的误差，本文开发了一个扩展的动态模型，并通过比较标准动态模型和扩展动态模型下卡尔曼滤波器对模拟数据的响应性能来证明其有效性。结果表明，在实际应用中，所提出的扩展动态模型优于标准动态模型，主要是因为它能够适应更大范围的动态条件，从而保证了卡尔曼滤波器的优化，从而产生可靠的定位结果。
The main problems faced by a dynamic model within a Kalman filter occur when the system experiences unexpected dynamic conditions, a change in data acquisition rate, or when the dynamics of the system are non-linear. To minimize the errors produced from dynamic modelling in unusual conditions, an extended dynamic model is developed in this paper, and its usefulness demonstrated through comparison of the performance of a Kalman filter's response to simulated data with a standard dynamic model and the extended dynamic model. The results show that, in use, the proposed extended dynamic model is superior to a standard dynamic model, due mainly to its ability to adapt to a wider range of dynamic conditions, which in turn ensures the optimization of the Kalman filter and the consequent generation of reliable positioning results.