GPS Fault Detection with IMU and Aircraft Dynamics

Abstract

Approaches with vertical guidance (APV) can provide greater safety and cost savings to general aviation through accurate GPS horizontal and vertical navigation. However, GPS needs augmentation to achieve APV fault detection (FD) requirements. Aircraft-based augmentation systems (ABAS) fuse GPS with additional sensors at the aircraft. Typical ABAS designs assume high-quality inertial sensors with Kalman filters but these are too expensive for general aviation. Instead of using high-quality (and expensive) sensors, the purpose of this paper is to investigate augmenting GPS with a low-quality micro electro-mechanical system (MEMS) inertial measurement unit (IMU) and aircraft dynamic model (ADM). The IMU and ADM are fused together using a multiple model fusion strategy in a bank of extended Kalman filters (EKF) with the normalized solution separation (NSS) FD scheme. A tightly-coupled configuration with GPS is used and frequent GPS updates are applied to the IMU and ADM to compensate for their errors. Based upon a simulated APV approach, the performance of this architecture in detecting a GPS ramp fault is investigated, showing a performance improvement over a GPS-only snapshot implementation of the NSS method. The effect of fusing the IMU with the ADM is evaluated by comparing a GPS-IMU-ADM EKF with a GPS-IMU EKF, where a small improvement in protection levels is shown.