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Low-Cost Multi-Sensor Data Fusion for Unmanned Aircraft Navigation and Guidance

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Abstract (2. Language): 
Multi-sensor navigation systems involving satellite-based and inertial sensors are widely adopted in aviation to improve the stand-alone navigation solution for a number of mission- and safety-critical applications. However such integrated Navigation and Guidance Systems (NGS) do not meet the required level of performances in all flight phases, specifically for precision approach and landing tasks. In this paper an innovative Unscented Kalman Filter (UKF) based NGS architecture for small-to-medium size Unmanned Aircraft (UA) is presented and compared with a standard Extended Kalman Filter (EKF) based design. These systems are based on a novel integration architecture exploiting state-of-the-art and low-cost sensors such as Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical System (MEMS) based Inertial Measurement Unit (IMU) and Vision Based Navigation (VBN) sensors. A key novelty aspect of this architecture is the adoption of Aircraft Dynamics Models (ADM) to compensate for the MEMS-IMU sensor shortcomings in high-dynamics attitude determination tasks. Furthermore, the ADM measurements are pre-filtered by an UKF so as to increase the ADM validity time in the UKF based system. The improvement in Position, Velocity and Attitude (PVA) measurements is due to the accurate modeling of aircraft dynamics and integration of VBN sensors. Based on the mathematical models described, the UKF based VBN-IMU-GNSS-ADM (U-VIGA) is implemented and compared with the EKF based system (E-VIGA) in a small UA integration scheme exploring a representative cross-section of the operational flight envelope, including high dynamics manoeuvres and CAT-I to CAT-III precision approach tasks. Simulation of the U-VIGA system shows improved results when compared to E-VIGA, owing to an increase in the validity time of the ADM solution for all flight phases. The proposed NGS architectures are compatible with the Required Navigation Performance (RNP) specified in the various UA flight phases, including precision approach tasks.
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REFERENCES

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