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首页> 外文会议>Saint Petersburg International Conference on Integrated Navigation Systems; 20070528-30; Saint Petersburg(RU) >ECONOMICAL ALGORITHMS FOR DETECTION AND ISOLATION OF INFORMATION FAULTS IN NAVIGATION COMPLEXES
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ECONOMICAL ALGORITHMS FOR DETECTION AND ISOLATION OF INFORMATION FAULTS IN NAVIGATION COMPLEXES

机译：导航复杂度中检测和隔离信息故障的经济算法

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摘要

Diversity of types of information faults in navigation complexes makes the development of algorithms for fault detection and isolation to be realized in the on-board computer complicated. Moreover, a complete list of possible types of faults may be unknown. Two algorithms are suggested to overcome these difficulties. The first algorithm presumes a set of types of faults to be known. It employs an augmented Kalman filter (AKF) that estimates a group of possible faults and allows the amount of computations to be reduced. It has been shown that the results of the AKF application allow derivation of a posteriori probabilities and estimates of particular faults as well as estimates of additional errors in navigation parameters caused by faults. These estimates can be used to recover the faulty system. The second algorithm does not require knowledge about types of faults and is intended to detect the system of the complex that has errors, anomalous in level and behavior, and to compensate for these errors. The efficiency of the algorithms developed is supported by the results of simulation and bench tests of the navigation complex including more than one inertial system.
机译：导航系统中信息故障类型的多样性使得在车载计算机中实现故障检测和隔离的算法的开发变得复杂。此外，可能的故障类型的完整列表可能是未知的。建议使用两种算法来克服这些困难。第一种算法假定一组已知的故障类型。它采用了增强的卡尔曼滤波器（AKF），可估计一组可能的故障并减少计算量。已经显示出，AKF应用的结果允许导出后验概率和特定故障的估计以及由故障引起的导航参数的附加误差的估计。这些估计值可用于恢复故障系统。第二种算法不需要有关故障类型的知识，并且旨在检测具有错误，级别和行为异常的复杂系统，并补偿这些错误。包括一个以上惯性系统的导航系统的仿真和基准测试结果支持了所开发算法的效率。

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