SYSTEMS AND METHODS FOR ATTITUDE FAULT DETECTION BASED ON INTEGRATED GNSS/INERTIAL HYBRID FILTER RESIDUALS

摘要

Systems and methods for attitude fault detection based on integrated GNSS/inertial hybrid filter residuals are provided. In one embodiment, a fault detection system for aircraft attitude measurement system comprises: a sensor monitor coupled to a first inertial measurement unit, the sensor monitor comprising: a navigation error model for the first inertial measurement unit, the model configured to model a plurality of error states including at least an attitude error state vector, an velocity error state vector, and a position error state vector determined from data generated by the first inertial measurement unit; and a propagator-estimator configured to propagate and update error states based on GNSS data; and a residual evaluator configured to input measurement error residual values generated by the propagator-estimator, wherein the residual evaluator outputs an alert signal when the measurement error residual values exceed a threshold.

主权项

1. A fault detection system for aircraft attitude measurement system, the fault detection system comprising:
a sensor monitor coupled to a first inertial measurement unit of the aircraft attitude measurement system, the sensor monitor comprising:
a navigation error model for the first inertial measurement unit, the navigation error model configured to model a plurality of error states including at least an attitude error state vector, an velocity error state vector, and a position error state vector determined from data generated by the first inertial measurement unit; anda propagator-estimator configured to propagate and update the plurality of error states from the navigation error model based on GNSS data; and a residual evaluator configured to input measurement error residual values generated by the propagator-estimator, wherein the residual evaluator outputs an alert signal when the measurement error residual values exceed a predetermined statistical threshold.