Research On Ultra-wideband Indoor Ranging And Localization Algorithm

With the development of modern wireless location technology,people have higher requirements for location service.In the open outdoor,the Beidou System and the GPS(Global Positioning System)can provide high-quality Positioning services for people,but in the complex indoor environment can not meet people's precision needs.Due to its advantages of high resolution,strong anti-multipath ability,low power consumption and good confidentiality,ultra-wideband technology has become a research hotspot in the field of indoor high-precision positioning.This paper studies indoor ranging and positioning algorithm based on UWB,and the main contents are summarized as follows:(1)The indoor ranging method based on TOF(Time of Flight)is studied.SDS-TWR(Symmetrical double-sided Two Way Ranging)based on TOF requires a long Time to distance and TDOA(Time Difference of Arrival)has a large ranging error.This paper presents the improved TDOA(Time Difference of Arrival)/SDS-TWR joint ranging algorithm,which divides the anchor node into the master node and the auxiliary node.TDOA ranging method is adopted from the auxiliary node to the label node and the master node,which can directly measure the Time Difference information between the label node and the auxiliary node.SDS-TWR ranging method with only one delay is used between master node and label node.In this paper,the variation of ranging error in TDOA/SDS-TWR and tag node clock offset is simulated by MATLAB modeling.The results show that the proposed TDOA/SDS-TWR joint ranging algorithm is effective,with high robustness of clock offset,less time consumption and good ranging accuracy,and the ranging error is within 0.25 m.(2)The indoor location algorithm based on TDOA is studied.In order to solve the problem that the improper selection of initial position in Taylor series expansion method would lead to non-convergence of the algorithm,C-Taylor algorithm was proposed.In this algorithm,the Chan algorithm was used to calculate the initial position of the tag nodes,and then the initial position was substituted into Taylor algorithm for iteration,and the final position coordinates of the tag nodes were obtained by weighting coefficient calculation.Matlab simulation shows that: 1)Compared with the traditional Chan algorithm and Taylor series expansion method,the proposed C-Taylor algorithm has higher positioning accuracy for indoor fixed labels and indoor mobile labels;2)C-Taylor algorithm uses Kalman optimization,that is,the estimated position of label nodes obtained by C-Taylor algorithm is taken as the preliminary estimate of Kalman filter,and the optimal position coordinates of label nodes are calculated by the optimal estimate obtained in the last round and this estimate,which significantly improves the positioning accuracy of indoor mobile label.