Date of Award
3-16-2009
Document Type
Thesis
Degree Name
Master of Science in Electrical Engineering
Department
Department of Electrical and Computer Engineering
First Advisor
Michael J. Veth, PhD
Abstract
In the recent past, a shift has taken place from manned to unmanned Intelligence, Surveillance, and Reconnaissance (ISR) missions. This shift has lead to an increase in the number of unmanned vehicles (UV) operating in a theater. Additionally, removal of the crew allows for a reduction in vehicle scale, which leads to an increased ability to operate in GPS degraded environments. With the loss of GPS signals the vehicles must rely on Inertial Navigation Systems (INS) which when reduced to an appropriate size are inherently inaccurate. This research endeavors to exploit three attributes of increased UV use for ISR missions. These attributes are: increased numbers of UVs, on-board vision, and wireless communications. This research’s focus is the development and validation of a cooperative navigation system based on the measurement of UV position relative to shared landmark position estimates. Each UV in the network locates landmarks using its on-board vision system and transmits the data to all other system UVs. After receiving data from the other UVs, the system fuses the landmarks with on-board measurements using a federated filter architecture. The system is evaluated using Matlab® simulation. Simulations of the cooperative system, with and without ranging, are compared to a non-cooperative simulation. The comparison is performed using four platform motion scenarios: stationary, linear, angular, and full motion. The simulation results demonstrate position error estimate improvements of 0.5 cm to 1 cm. Additionally, the stationary and linear motion scenarios demonstrate attitude observability difficulties eliminated by the introduction of angular motion.
AFIT Designator
AFIT-GE-ENG-09-05
DTIC Accession Number
ADA500845
Recommended Citation
Bingham, Jason K., "Vision-Aided Cooperative Navigation for Multiple Unmanned Vehicles" (2009). Theses and Dissertations. 2475.
https://scholar.afit.edu/etd/2475