INS-GPS Integration System for Soldier Positioning
Tutor / director / avaluadorHoekstra, Gerard
Tipus de documentProjecte/Treball Final de Carrera
Condicions d'accésAccés restringit per acord de confidencialitat
Today positioning technologies have become one of the most intensive researching fields. Most of the current operating systems focus on the group of GNSS (Global Navigation Satellite Systems), among which GPS is the most used. However, in certain scenarios, e.g. inside buildings, GPS is not reliable enough since satellites signals are seriously distorted. Therefore, human location applications demand other alternative techniques to overcome this constraint. One of them is Inertial Navigation technology. An Inertial Navigation System (INS) is a system that provides positioning information by using so-called inertial sensors. Although INS contribute to overcome some of the constraints of GNSS, its operation as an autonomous system is very limited due to the nature of the sensors they use. INSs are well-known to be accurate systems during short periods of time, but their accuracy drift over time. However, an emerging system concept based on integrating INS and GPS has become a feasible solution to fuse the advantages of both INS and GPS in order to overcome their individual drawbacks. The present thesis focuses on investigating and developing an INS-GPS integration system. First, this report aims the operation principles and all factors involved in developing an INS. An INS prototype implementation, based on MEMS sensors, has been carried out and the system has been tested in several kinds of scenarios. Second, the INS-GPS integration system basics are discussed, putting emphasis on the Kalman Filter, which is the integration system core. The INS-GPS integration prototype implemented in this project is based upon a loosely coupled architecture. The system has been also tested under diferent conditions. All tests and results of both system prototypes are shown. Finally, all results are analysed in order to have understanding about the performance of each system, and a comparison between both prototypes is done, while remarking the benefits and drawbacks of the systems implemented. The conclusions drawn out from these analyses are explained and several fields that may be worth investigating to keep improving the developed solutions are commented too.
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