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首页> 外文期刊>International journal for uncertainty quantifications >UNCERTAINTY QUANTIFICATION TOWARDS FILTERING OPTIMIZATION IN SCENE MATCHING AIDED NAVIGATION SYSTEMS
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UNCERTAINTY QUANTIFICATION TOWARDS FILTERING OPTIMIZATION IN SCENE MATCHING AIDED NAVIGATION SYSTEMS

机译：场景匹配辅助导航系统中优化滤波的不确定性量化

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摘要

There exist many uncertain sources for positioning process of scene matching aided navigation systems, and filter architecture and random parameters are considered mainly in this paper for the goal of trajectory optimization. In order to reduce the uncertainty of filter architecture, a practical scene matching optimization scheme is proposed, where fusion architecture and filtering parameters are both considered, in the circumstance of different sampling rates without transmission delay. The matching interval is determined by adjustment time of matching, matching points are settled from back to front, a cost function for the matching number is designed according to optimization criteria, and finally an appropriate matching number is determined by required mapping accuracy. The optimization scheme is validated by the simulation. On the other hand the filtering parameters are identified and validated by reducing parameter space in advance and local sensitivity analysis method. Simulation results illustrate that the systems are more sensitive for the measurement noise, which provides a theoretical basis for engineering applications.
机译：场景匹配辅助导航系统的定位过程存在很多不确定性来源，本文主要考虑滤波器的结构和随机参数以达到轨迹优化的目的。为了减少滤波器架构的不确定性，提出了一种实用的场景匹配优化方案，在不考虑传输延迟的情况下，采用不同的采样率，同时考虑融合架构和滤波参数。通过匹配的调整时间确定匹配间隔，从前到后确定匹配点，根据优化标准设计匹配数的代价函数，最后根据所需的映射精度确定合适的匹配数。仿真验证了该优化方案。另一方面，通过提前减少参数空间和局部灵敏度分析方法来识别和验证滤波参数。仿真结果表明，该系统对测量噪声更加敏感，为工程应用提供了理论依据。

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