2011 · 16 citations · 16 references
EngineeringLand VehiclesLocation EstimationDigital CompassMulti-sensor Information FusionPrecision NavigationMultimodal Sensor FusionSystems EngineeringDirection Cosine MatrixKinematicsSensor FusionInclinometerLinear Process ModelAutomatic NavigationInertial SensorsMulti-sensor ManagementData FusionMechatronicsVehicle LocalizationOrientation EstimationAerospace EngineeringOdometryRemote SensingMulti-sensor Data Fusion
The study presents an orientation estimation algorithm for land vehicles based on the Direction Cosine Matrix (DCM) method. The algorithm employs two Kalman filters to estimate rotation matrix elements, a rule‑based decision structure to select the optimal measurement from GPS and a digital compass, and incorporates vehicle dynamics to mitigate the compass’s slow response. When evaluated on real‑time logged data and under simulated GPS outages, the algorithm accurately estimates attitude and heading angles, demonstrating robust performance across sensor failures.
In this paper, an algorithm estimating orientation is implemented using Direction Cosine Matrix (DCM) method, chosen due to its linear process model and ease of use. Two Kalman filters were used to estimate the rotation matrix elements where the Euler Angles are easily computed. A rule based decision structure is used to choose the best measurement available in the system from GPS and digital compass. Also the dynamic motion of the vehicle is considered to overcome the slow response of the digital compass. The algorithm is tested with real time logged data set and a decision structure is developed to have the best Information provided from the multiple sensors. The algorithm is also tested under artificial GPS outages, performs successfully for both attitude and heading angles.
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A Curved-Beam Bistable Mechanism
J. Qiu, J.H. Lang, Alex Slocum · Journal of Microelectromechanical Systems · 2004 · 790 citations