Indoor Location Technology Research Based On Ultra-wideband

With the improving demand for navigation and positioning, high-precision indoor localizationtechnology is becoming more and more important spot of study. Because of the complexity of theindoor environment, the radio small scale fading phenomenon is very serious, which would affect thelocalization accuracy and limits the adoption of the localization. After FCC open the UWB (Utral-wideband) technology, there were obvious progress with the indoor localization research. Because ofits high resolution, low power consumption, high multipath recogonition and anti-interference ability,UWB is very suitable for locating under the indoor environment.There is two step for indoor localization: first, using localization method based on time of arrival,time difference of arrival time, angle of arrival or receive signal strenth to obtain the value of positionmeasurement, localization algorithm is then used to computing the value of measure and eventuallyget the position of the node to be located. For indoor location, the most important assessment indicatoris positioning accuracy, and the robustness of the technology. The study using existing research resultbased on UWB in LOS environment of indoor positioning can achieve a high accuracy, but still notvery well under the NLOS(Non-line-of-sight) environment.The thesis focuses on the research of uwb indoor positioning technology related techniques, byreading the vast amount of literature, we introduces the UWB indoor positioning technology basedon UWB indoor channel model of IEEE802.15.4a. The localization method based on TOA, TDOAand AOA technology is introduced and analyzed in detail. The Fang, Chan’s, Taylor and othercommonly used localization algorithm is simulated to have a deep understand of those algorithm, inorder to acknownledge the algorithm performance on integrated chip processor, the time complexityis measured and then compared to each other. We also proposes a NLOS identification and mitigationmethod based on statistics data, the method can recognize the indoor NLOS path by the rate of90%,by using the recognition value of likelihood function value, a weighted least square algorithm isproposed, it can greatly improve the positioning accuracy in indoor environment with NLOS paths.The performance of the algorithm in time complexity is also very good, which can be suitable to runon integrated chip.