Development of positioning systems: Satellite- based positioning and terrestrial- based positioning

Nowadays, global positioning system (GPS) is utilized broadly in the world, but performance can be substantially degraded in a multipath and non-line of sight (NLOS) environments. Since the multipath can present indecorous errors of the received signal with deformation of the phase and delay that preclude the accurate approximation of the receiver position. The power of the GPS signal will be weakened, and its reliability and position accuracy will be degraded much in the low signal to noise ratio (SNR) environment that gives restrictions in terms of tracking performance. In this thesis, the receiver's structure of a GPS has been modified using GPS repeaters to ameliorate the indoor positioning performance and the quality of the GPS signal reception. Also, we suggested a modified particle filter (MPF) that can approximate the entire parameters and produces preferable model fit which is compared to alternative estimation procedures. Based on adaptive particle filter (PF), a filtering algorithm has been proposed to improve the positioning accuracy of GPS receiver and to solve the error of GPS positioning. The experimental results show that for long periods of time, the system is capable to give an accurate outdoor and indoor positioning. Also, indoor location based on active RFID technologies has been studied. Due to the multipath propagation and random noise interference of complex indoor environment, for the pursuit of higher localization accuracy, an optimized algorithm has been suggested to negotiate some insufficiency in LANDMARC and VIRE algorithms. The boundary virtual reference (BVIRE) tag that relates to the overall system precision is ameliorated and a new error correction model is established. In the experiments, it is seen that the proposed algorithm is effective and precise compared with other algorithms.