Multi-sensor data fusion techniques for RPAS navigation and guidance
作者： Francesco Cappello , Roberto Sabatini , Subramanian Ramasamy
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摘要: Integrated Navigation and Guidance Systems (NGS) based only on satellite other lowcost navigation sensors (e.g., Micro-Electro-Mechanical System (MEMS) inertial sensors) cannot guarantee the Required Performance (RNP) in all flight phases of Remotely Piloted Aircraft (RPAS). In this paper, a novel NGS for small-to-medium size RPAS is presented, which Global Satellite (GNSS), Vision Based (VBN) low-cost avionics sensors. Additionally, Dynamics Model (ADM) used to compensate MEMS Inertial Measuring Unit (IMU) sensor shortcomings high-dynamics attitude determination tasks. Two multi-sensor architectures are compared that an Extended Kalman Filter (EKF) Unscented (UKF) approach data fusion. The ADM measurements prefiltered by UKF increase solution validity time. EKF VBNIMU- GNSS-ADM (E-VIGA) system (U-VIGA) performances evaluated small integration scheme (i.e., AEROSONDE platform) exploring representative cross-section operational envelope. error covariance analysis performed (ADF) using Monte Carlo simulation. position accuracy comparison shows E-VIGA U-VIGA systems fulfill relevant RNP criteria, including precision down CAT-II.
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