Research Of Indoor Positioning Technology Based On Chirp

With the rapid development of wireless network technology and the rapidincrease of smart business, wireless location service has been gotten more and moreattention. From the common scientific research, business, military service, until theemergency search and rescue, location service has important applications. Because ofthe presence of serious obstacles, non line-of-sight transmission in the indoorenvironment, the noises make the positioning accuracy of infrared technology andultrasonic technology drop. We need to find a new positioning technology to meet theprecision requirement.Linear frequency modulation signal，which is referred to as Chirp signal，with itsadvantages of high precision, low power consumption, strong penetrating power,becomes the emerging wireless location technology. And for its transmission distance,easy autocorrelation de-modulation, anti-multipath interference capability and lowemission energy, in high dense multipath indoor environment positioning Chirp hasbeen got more and more extensive research. In this paper, the main work is as follows:First of all, on the basis of summarizing the current indoor positioningtechnology research status at home and abroad, this paper introduces the significanceand the research content, the advantages and disadvantages of several commonpositioning methods. This paper introduced the positioning error of CRLB, andexpounds several factors affected the accuracy of positioning.Secondly, this paper introduces the IEEE802.15.4a channel model, the Chirp‘scharacteristics of time domain and frequency domain. Paper introduces the nanoLOCsystem based on it, expounds the analysis of system structure and principle.Finally, under the analysis of the actual positioning environment, paper buildsthe nanoLOC system platform. Aiming at the non-monotone defect of the localmeasurements, the paper proposes the I-VIRE method which combines the VIREalgorithm with fingerprint algorithm, using the moving least squares method forfitting the measured data to get “distance-time” model. At last, the algorithm uses theweighting factor and secondary positioning method to achieve the final positioning.The simulation results show that the algorithm not only improves the locationaccuracy of VIRE algorithm, also effectively reduces the early large workload offingerprint algorithm.