A Study On Indoor Positioning Algorithm Based On Ultra-wideband Technology

With the beginning and fast development of the internet of things and theconstruction of intelligent city, location-based-service (short for LBS) is widely usedincreasingly. As one of the LBS’s core technologies, the indoor position is animportant part of it. This thesis advances two kinds of high real-time, high robustness,and high precision indoor location algorithms, which are based on Impulse RadioUltra Wideband (short for IR-UWB) orientation technology.This thesis analyses the indoor transportation model of UWB signal at first, andstudies the orientation solutions based on distances of UWB orientation system,finally, the distance measurement solution of advanced TOA(time of arrival)-TWR(Two Way Ranging) is adopted, which solves TOA-OWR(One Way Ranging)’sthe actual problem of difficulty and high costs brought by all of the target nodes andanchor nodes’ need for time synchronization, consequently, it makes the two indoororientation algorithms more practical.It is found that the distance error brought by multipath effect andnon-line-of-sight(NLOS) in the process of IR-UWB signal’s transportation during theresearch into indoor orientation algorithms based on TOA distance measurement is themain reason for the decrease of orientation precision, and the error accords withGauss distribution in most situations. Therefore, this thesis advances UWB indoorlocation algorithm based on Wavelet analysis and Full Centroid Position scheme,decreasing the distance error and making full use of the insensitivity to distances ofFull Centroid Position scheme. What’s more, the algorithm can offer more preciseorientation result by only three anchor nodes and few data.Through further analysis, it is found that the distance error mentioned in theprevious paragraph may accord with one of the other three distributions in fewersituations except for Gauss distribution, which are Exponential distribution,Uniformity distribution, and Rayleigh distribution. Thus, this thesis also advances UWB indoor location algorithm based on EEMD (the shortened form of EnsembleEmpirical Mode Decomposition) and Full Centroid Position scheme; accordingly,more precise orientation result and better robustness are attained.