Frequency Modulated Continuous Wave Radar and Video Fusion for Simultaneous Localization and Mapping
Fred Garber (Committee Member), Arthur Goshtasby (Committee Member), Lang Hong (Advisor), Richard Martin (Committee Member), Kefu Xue (Committee Member)
Doctor of Philosophy (PhD)
There has been a push recently to develop technology to enable the use of UAVs in GPS-denied environments. As UAVs become smaller, there is a need to reduce the number and sizes of sensor systems on board. A video camera on a UAV can serve multiple purposes. It can return imagery for processing by human users. The highly accurate bearing information provided by video makes it a useful tool to be incorporated into a navigation and tracking system. Radars can provide information about the types of objects in a scene and can operate in adverse weather conditions. The range and velocity measurements provided by the radar make it a good tool for navigation.
FMCW radar and color video were fused to perform SLAM in an outdoor environment. A radar SLAM solution provided the basis for the fusion. Correlations between radar returns were used to estimate dead-reckoning parameters to obtain an estimate of the platform location. A new constraint was added in the radar detection process to prevent detecting poorly observable reflectors while maintaining a large number of measurements on highly observable reflectors. The radar measurements were mapped as landmarks, further improving the platform location estimates. As images were received from the video camera, changes in platform orientation were estimated, further improving the platform orientation estimates. The expected locations of radar measurements, whose uncertainty was modeled as Gaussian, were projected onto the images and used to estimate the location of the radar reflector in the image. The colors of the most likely reflector were saved and used to detect the reflector in subsequent images. The azimuth angles obtained from the image detections were used to improve the estimates of the landmarks in the SLAM map over previous estimates where only the radar was used.
Department or Program
Ph.D. in Engineering
Year Degree Awarded
Copyright 2012, all rights reserved. This open access ETD is published by Wright State University and OhioLINK.