The design, realization, and experimental validation of an original avionic attitude estimation unit are presented. The core of the system is a nine-state extended Kalman filter that optimally blends complementary kinematic data provided by orthogonal triads of inertial micro-electro-mechanical systems sensors: rate gyros (short-term fast dynamics) and accelerometers (long-term static reference). The unit is embedded in a novel aircraft emergency guidance system based on miniaturized solid-state sensors. While achieving the required extreme compactness, state-of-the-art performance is preserved: 50 Hz update rate, 0.1 degrees angular resolution, 0.5 degrees static accuracy, and 2 degrees dynamic accuracy (400 degrees/s max. angular rate, 10 g max. acceleration), all experimentally verified and granted over the extended thermal range. The selection of the state variables has been carefully trimmed in order to maximize the performance/speed tradeoff for real-time running in an embedded processor. The adoption of the Kalman observer also enables the implementation of model-based sensor fault detection with no extra computational cost.

Real-Time Data Fusion and MEMS Sensors Fault Detection in an Aircraft Emergency Attitude Unit Based on Kalman Filtering

CARMINATI, MARCO;FERRARI, GIORGIO;SAMPIETRO, MARCO
2012

Abstract

The design, realization, and experimental validation of an original avionic attitude estimation unit are presented. The core of the system is a nine-state extended Kalman filter that optimally blends complementary kinematic data provided by orthogonal triads of inertial micro-electro-mechanical systems sensors: rate gyros (short-term fast dynamics) and accelerometers (long-term static reference). The unit is embedded in a novel aircraft emergency guidance system based on miniaturized solid-state sensors. While achieving the required extreme compactness, state-of-the-art performance is preserved: 50 Hz update rate, 0.1 degrees angular resolution, 0.5 degrees static accuracy, and 2 degrees dynamic accuracy (400 degrees/s max. angular rate, 10 g max. acceleration), all experimentally verified and granted over the extended thermal range. The selection of the state variables has been carefully trimmed in order to maximize the performance/speed tradeoff for real-time running in an embedded processor. The adoption of the Kalman observer also enables the implementation of model-based sensor fault detection with no extra computational cost.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/693526
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