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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Single-Filter Finite Fault Detection and Exclusion Methodology for Real-Time Validation of Plug-and-Play Sensors
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Single-Filter Finite Fault Detection and Exclusion Methodology for Real-Time Validation of Plug-and-Play Sensors

机译：单滤器有限故障检测和排除方法，用于即插即用传感器的实时验证

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摘要

All-source navigation has become increasingly relevant over the past decade with the development of viable alternative sensor technologies. However, as the number and type of sensors informing a system increases, so does the probability of corrupting the system with sensor modeling errors, signal interference, and undetected faults. Though the latter of these has been extensively researched, the majority of existing approaches have designed algorithms centered around the assumption of simultaneously redundant, synchronous sensors with well-understood measurement models, none of which are guaranteed for all-source systems. As part of an overall all-source assured or resilient navigation objective, this research contributes a key component-validation of sensors which have questionable sensor models, in a fault-agnostic and sensor-agnostic manner, and without compromising the ongoing navigation solution in the process. The proposed algorithm combines a residual-based test statistic with the partial update formulation of the Kalman-Schmidt filter to provide a reliable method for sensor model validation that protects the integrity of the navigation solution during the validation process, all using only a single existing filter. The performance of the proposed method is validated against traditional fault detection and exclusion methods (such as normalized solution separation and conventional residual sequence monitoring) using Monte-Carlo simulations in a 2D non-Global Positioning System navigation problem with a plug-and-play position sensor.
机译：随着可行替代传感器技术的发展，全源导航在过去十年中越来越相关。然而，随着通知系统的传感器的数量和类型增加，损坏系统具有传感器建模误差，信号干扰和未检测到的故障的概率。虽然这些已经广泛研究了这些方法，但大多数现有方法都设计了围绕着假设同时冗余的同步传感器的设计算法，其具有良好的测量模型，其中都没有保证全源系统。作为整体全源保证或弹性导航目标的一部分，该研究贡献了传感器的关键组件验证，该传感器具有可疑的传感器模型，以故障不可行的和传感器无话的方式，并且在不损害正在进行的导航解决方案的情况下过程。该算法将基于残差的测试统计与Kalman-Schmidt滤波器的部分更新配方组合起来，为传感器模型验证提供了可靠的方法，该方法可以在验证过程中保护导航解决方案的完整性，只使用单个现有过滤器。通过在2D非全球定位系统导航问题中使用Monte-Carlo模拟，验证了所提出的方法的性能，以防止在2D非全球定位系统导航问题中使用蒙特-Carlo仿真与即插即用位置传感器。

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