The Inertial Navigation System (INS) is often fused with the Global Navigation Satellite System (GNSS) to provide more robust and superior navigation service, especially in degraded signal environments. Compared with loosely and tightly coupled architectures, the Deep Integration (DI) architecture has better tracking and positioning performance. Information is shared among channels, and the assistant information from INS helps to reduce the dynamic stress of tracking loops. However, this vector tracking architecture may result in easy propagation of errors among tracking channels. To solve this problem, a Fault Detection and Exclusion (FDE) method for the deeply integrated BeiDou Navigation Satellite System (BDS)/INS navigation system is proposed in this paper. This method utilizes pre-filters' outputs and integration filter's estimations to form test statistics. These statistics can help to detect and exclude both step errors and Slowly Growing Errors (SGEs) correctly. The monitoring capability of the method was verified by a simulation which was based on a software receiver. The simulation results show that the proposed FDE method works effectively. Additionally, the method is convenient to be implemented in real-time applications because of its simplicity.

中文翻译：

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深度集成的BDS / INS系统的故障检测和排除方法。

惯性导航系统（INS）通常与全球导航卫星系统（GNSS）融合在一起，以提供更强大，更出色的导航服务，尤其是在信号质量下降的环境中。与松散和紧密耦合的体系结构相比，深度集成（DI）体系结构具有更好的跟踪和定位性能。信息在通道之间共享，并且来自INS的辅助信息有助于减少跟踪循环的动态压力。但是，这种矢量跟踪体系结构可能会导致在跟踪通道之间轻松传播错误。针对这一问题，本文提出了一种深度集成北斗导航卫星系统（BDS）/ INS导航系统的故障检测与排除方法。该方法利用了前置滤波器的输出和积分滤波器的 估计以形成测试统计量。这些统计信息可以帮助正确检测和排除步进错误和缓慢增长错误（SGE）。通过基于软件接收器的仿真，验证了该方法的监视能力。仿真结果表明，所提出的FDE方法是有效的。另外，由于其简单性，该方法便于在实时应用中实施。