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Full-Text Articles in Engineering
Design And Characterization Of A Low Cost Mems Imu Cluster For Precision Navigation, Daniel R. Greenheck
Design And Characterization Of A Low Cost Mems Imu Cluster For Precision Navigation, Daniel R. Greenheck
Master's Theses (2009 -)
The fast paced development of micro-electromechanical systems (MEMS) technology in recent years has resulted in the availability of low cost gyroscopes and accelerometers in commercial markets. These sensors can be integrated into a single device known as an inertial measurement unit (IMU). An IMU is capable of tracking and navigating a vehicle for a short period of time in the absence of external position and attitude updates. The precision of the manufacturing techniques used to fabricate commercial MEMS sensors as well as their mechanical nature result in noise and errors that limit their performance. It has been mathematically shown that …
Initial Implementation And Testing Of A Tightly-Coupled Imu/Pseudolite System, James E. C. Kawecki
Initial Implementation And Testing Of A Tightly-Coupled Imu/Pseudolite System, James E. C. Kawecki
Theses and Dissertations
Currently, the 746th Test Squadrons (746th TS) Central Inertial and GPS Test Facility (CIGTF) operates one of the most accurate truth reference systems, called the CIGTF Reference System (CRS). CIGTF will be replacing the CRS with a new references system called UHARS (Ultra High Accuracy Reference System). UHARS will differ from CRS by adding the ability to use a non-GPS pseudolite system, as a new measurement source. This research effort describes the design of the extended Kalman filter which is developed in AFIT's SPIDER filter framework which implements a tightly-coupled pseudolite/INS filter.
Urban Environment Navigation With Real-Time Data Utilizing Computer Vision, Inertial, And Gps Sensors, Johnathan L. Rohde
Urban Environment Navigation With Real-Time Data Utilizing Computer Vision, Inertial, And Gps Sensors, Johnathan L. Rohde
Theses and Dissertations
The purpose of this research was to obtain a navigation solution that used real data, in a degraded or denied global positioning system (GPS) environment, from low cost commercial o the shelf sensors. The sensors that were integrated together were a commercial inertial measurement unit (IMU), monocular camera computer vision algorithm, and GPS. Furthermore, the monocular camera computer vision algorithm had to be robust enough to handle any camera orientation that was presented to it. This research develops a visual odometry 2-D zero velocity measurement that is derived by both the features points that are extracted from a monocular camera …