2008 · 492 citations · 19 references
EngineeringAerial RoboticsNonlinear Complementary FilterAerospace EngineeringAir Vehicle SystemAircraft NavigationMechatronicsHigh Frequency EstimationSpacecraft Attitude ControlFlying RobotKinematicsRaw Accelerometer OutputComplementary FilterFlight Control
Accelerometer readings on a fixed‑wing UAV contain both gravitational and airframe acceleration components, especially during turns, complicating attitude estimation. This study investigates a nonlinear complementary filter for attitude estimation using only a low‑cost IMU on a fixed‑wing UAV. The filter fuses low‑frequency accelerometer data with high‑frequency gyrometer output, estimating airframe acceleration via a centripetal force model and angle‑of‑attack dynamics to isolate gravity. Experimental results on real‑world data evaluate the filter’s performance against a full GPS/INS system.
This paper considers the question of using a nonlinear complementary filter for attitude estimation of fixed-wing unmanned aerial vehicle (UAV) given only measurements from a low-cost inertial measurement unit. A nonlinear complementary filter is proposed that combines accelerometer output for low frequency attitude estimation with integrated gyrometer output for high frequency estimation. The raw accelerometer output includes a component corresponding to airframe acceleration, occurring primarily when the aircraft turns, as well as the gravitational acceleration that is required for the filter. The airframe acceleration is estimated using a simple centripetal force model (based on additional airspeed measurements), augmented by a first order dynamic model for angle-of-attack, and used to obtain estimates of the gravitational direction independent of the airplane manoeuvres. Experimental results are provided on a real-world data set and the performance of the filter is evaluated against the output from a full GPS/INS that was available for the data set.
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