Abstract
This paper investigates the navigation performance of a vehicle dynamic model-based (VDM-based) tightly coupled architecture for a fixed-wing Unmanned Aerial Vehicle (UAV) during a global navigation satellite system (GNSS) outage for real-time applications. Unlike an Inertial Navigation System (INS) which uses inertial sensor measurements to propagate the navigation solution, the VDM uses control inputs from either the autopilot system or direct pilot commands to propagate the navigation states. The proposed architecture is tested using both raw GNSS observables (Pseudorange and Doppler frequency) and Micro-Electro-Mechanical Systems-grade (MEMS) Inertial Measurement Unit (IMU) measurements fused using an extended Kalman filter (EKF) to aid the navigation solution. Other than the navigation states, the state vector also includes IMU errors, wind velocity, VDM parameters, and receiver clock bias and drift. Simulation results revealed significant performance improvements with a decreasing number of satellites in view during 140 seconds of a GNSS outage. With two satellites visible during the GNSS outage, the position error improved by one order of magnitude as opposed to a tightly coupled INS/GNSS scheme. Real flight tests on a small fixed-wing UAV show the benefits of the approach with position error being an order of magnitude better as opposed to a tightly coupled INS/GNSS scheme with two satellites in view during 100 seconds of a GNSS outage.
Highlights
Low-cost, low-mass Unmanned Aerial Vehicles (UAVs) have found significant applications in Dull Dangerous and Dirty “D-D-D” fields
The continued estimation of the biases even during the global navigation satellite system (GNSS) outage is attributed to the improved observability due to the use of the vehicle dynamic model (VDM)
With two satellites visible, the final root mean squared (RMS) of roll error for the VDM-based scheme increased by 25% to 0.15° while for the inertial navigation system (INS)-based it increased by a factor of 6 to 0.36°
Summary
Low-cost (sub $12,000), low-mass (sub 20 kg) Unmanned Aerial Vehicles (UAVs) have found significant applications in Dull Dangerous and Dirty “D-D-D” fields. Khaghani and Skaloud [10], and Mwenegoha et al [11] extended the model-based approach proposed by Sendobry to fixed-wing UAVs. Simulation results revealed two orders of magnitude improvement in position estimation during extended GNSS outages. The navigation performance with decreasing number of satellites in view was not investigated because the proposed schemes relied on filtered GNSS measurements (position, velocity) which are not available during an outage. A specific case to a fixed-wing UAV is investigated which, alongside the raw observables, uses measurements from a low-cost MEMS-grade IMU to aid the navigation solution.
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