Abstract
Indoor positioning technology has been widely used in today’s life, but due to the influence of multipath effect, the positioning signal is attenuated or even interrupted seriously, resulting in obvious reduction or even failure of positioning accuracy. Therefore, the emerging multi-sensor joint positioning has become the general trend of the development of positioning technology, in which Ultra-Wide Band (UWB) and Inertial Measurement Unit (IMU) have their own features in positioning and navigation. So this paper combines the advantages of UWB and IMU to achieve accurate positioning in complex environment. Firstly, the signal transmission law in complex environment is obtained by distinguishing Line of Sight (LOS) from NLOS (Non Line of Sight) environment. Secondly, the maximum likelihood estimation algorithm is used to eliminate the influence of NLOS on the transmitted signal, and then the extended Kalman filter information fusion strategy is used. The ranging information of UWB and the angle information of IMU are fused to realize the accurate positioning of UWB in complex environment. Finally, the experimental results show that the performance of the joint positioning proposed in this paper is obviously better than that of a single sensor compared with single UWB and single IMU positioning. It provides more solutions for accurate indoor positioning of multi-sensor fusion.
Highlights
At present, outdoor positioning technology is developing faster and faster in response to market demand
(3) According to the transmission law of Ultra-Wide Band (UWB) signal information, the related signal information is extracted, and the maximum likelihood estimation algorithm is used to eliminate the influence of NLOS on the transmitted signal
Because UWB signal has high ranging accuracy and strong penetration ability, Inertial Measurement Unit (IMU) can carry out autonomous positioning and navigation according to acceleration, angle and other information, so this paper combines the advantages of ultra-wideband and IMU to achieve accurate positioning in complex environment
Summary
Scitation.org/journal/adv but it has corresponding limitations. The principle of ultrasonic ranging is detected by sound waves, and the transmission speed of sound waves is slow, so it will reduce the real-time positioning. 37–38, a NLOS discrimination algorithm based on support vector machine (SVM) is proposed, which is effective, but compared with the method proposed in this paper, it is relatively complex and has a large amount of computation in practical positioning applications. In the complex environment, how to automatically identify the number of received UWB anchor nodes and judge the ranging accuracy of the received UWB signal is not given On this basis, this paper continues to expand and in-depth research, to achieve a complex environment, the use of UWB and IMU joint positioning technology to improve the positioning accuracy in complex environment, for multi-sensor joint positioning to provide more solutions. In this paper, based on the existing results, a Kalman filter fusion method of UWB ranging information and IMU acceleration information is proposed to obtain more accurate personnel position information.
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