Gps/ins/pl/tls Integration Supporting Navigation of Geophysical Sensors for Unexploded Ordnance Detection and Discrimination

نویسندگان

  • Dorota A. GREJNER-BRZEZINSKA
  • Charles TOTH
  • Hongxing SUN
  • Xiankun WANG
  • Chris RIZOS
چکیده

The primary objective of the research presented here is to develop high-accuracy and high-reliability geolocation algorithms and to prototype a hybrid system based on multisensor integration to improve geolocation of geophysical sensors at munitions and explosives of concern (MEC) sites. The current methods used at MEC sites for buried unexploded ordnance (UXO) detection are extremely expensive and frequently provide unsatisfactory results, due mainly to the inability of current technology to discriminate between UXO and non-hazardous items. Consequently, about 90% of the total cost of MEC site remediation is on excavating objects that pose no threat. This project is expected to provide an improved geolocation capabilities of a portable geophysical mapping system in open and GPSchallenged environments, to ensure a better object discrimination from the collected imagery and, ultimately, to eliminate excavation of non-hazardous objects. This geolocation system, currently under development at The Ohio State University Satellite Positioning and Inertial Navigation (SPIN) Laboratory, is designed as a tight quadrupleintegration of the Global Positioning System (GPS), Inertial Navigation System (INS), a terrestrial RF system, often called a pseudolite (PL), and Terrestrial Laser Scanning (TLS). The key novel aspect of the proposed system is the TLS component, that can provide very high positioning accuracy in a local frame, and thus can support GPS/INS/PL-based navigation to achieve high-accuracy relative positioning in impeded environments. This paper concentrates on the concept design of the hybrid geolocation system, the algorithmic approach to sensor integration with a special emphasis on TLS integration with GSP/INS/PL, and the preliminary performance assessment based on simulated data.

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تاریخ انتشار 2008