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Comparison of federated and centralized Kalman filters with fault detection considerations

机译:考虑故障检测的联邦和集中式卡尔曼滤波器比较

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This paper examines the results obtained by simulating an aircraft navigation system with a partial complement of a typical avionics sensor array using two different techniques of estimation processes: the conventional Kalman and the federated filter architectures. Areas of interest include error state estimation accuracy, residual behavior under induced sensor failure conditions, and potential for failure detection and isolation. Several simulations were accomplished for each filter design and the results were compared in order to verify the validity of the recently developed federated filter architecture. Comparison of the error state estimation accuracies of the two filter designs revealed excellent overall performances for both. The identification of failures showed a definite advantage in the federated filter design. Having sensor-dedicated local filters allowed for easy sensor failure identification for the federated filter, while the centralized filter design suffered from navigation solution corruption. Once established as a valuable estimation technique, the federated filter will add significantly to the viable alternatives when choosing a filter architecture for avionics modifications or implementations.
机译:本文研究了通过使用两种不同的估计过程技术(传统的卡尔曼算法和联合滤波器体系结构)对典型航空电子传感器阵列的部分补充进行模拟的飞机导航系统所获得的结果。关注的领域包括错误状态估计的准确性,在感应式传感器故障条件下的残留行为以及故障检测和隔离的可能性。针对每种滤波器设计完成了几次仿真,并对结果进行了比较,以验证最近开发的联合滤波器体系结构的有效性。两种滤波器设计的误差状态估计精度的比较表明,两者均具有出色的整体性能。故障识别在联合过滤器设计中显示出一定的优势。使用传感器专用的本地过滤器可以轻松识别联邦过滤器的传感器故障,而集中式过滤器设计会遭受导航解决方案的损坏。一旦确立为有价值的估算技术,当为航空电子修改或实施选择滤波器架构时,联邦滤波器将大大增加可行的替代方案。

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