| There is a great need to develop non-GPS based methods for positioning and navigation in situations where GPS is not available. This research focuses on the development of an Ultra-Wideband Orthogonal Frequency Division Multiplexed (UWB-OFDM) radar as a navigation sensor in GPS-denied environments. A side-looking vehicle-fixed UWB-OFDM radar is mounted to a ground or aerial vehicle continuously collecting data. A set of signal processing algorithms and methods are developed which use the raw radar data to aide in calculating the vehicle position and velocity via a simultaneous localization and mapping (SLAM) approach. The radar processing algorithms detect strong, persistent, and stationary reflectors embedded in the environment and extract range/Doppler measurements to them. If the radar is the only sensor available, the measurements are used to directly compute the vehicle position via an extended Kalman filter (EKF) or Levenberg-Marquardt solver. If an existing navigation platform is available, the measurements are combined with the other sensors in an EKF. The developed algorithms are tested via both a series of airborne simulations and a ground-based experiment. The airborne simulations are performed with simulated commercial-grade, tactical-grade, and navigation-grade INS systems available. The experiment is performed with an indoor mobile platform containing an HG1700 tactical-grade INS and an X-band 500MHz UWB-OFDM radar. For all configurations, the computed navigation solution performance is analyzed with the following sensor availability: radar-only, INS-only, and combined radar/INS. In both simulation and experimental scenarios, the integrated INS/UWB-OFDM system shows significant improvements over an INS-only navigation solution. The radar-only system performs well assuming high availability of reflectors to track, with decreased performance when reflector-less environments are encountered. |
