UWB Hybrid Filtering-Based Mobile IoT Device Tracking

The positioning accuracy of UWB-based mobile Internet of Things (IoT) devices is frequently impacted by the complicated indoor environment, which is a common application for automated following mobile IoT devices. To address the issue of abnormal value errors such as high noise and UWB jitter value when tracking and locating mobile IoT devices in complicated indoor environments, this paper proposes to use a hybrid filtering weighted following algorithm based on UWB, which combines the benefits and drawbacks of Gaussian, median, and average filtering techniques, introduces the residual value of ranging, and combines geometric positioning to determine the ideal following value. The experimental results show that the proposed algorithm can effectively filter out the UWB error under multi-factor interference and finally estimate the UWB value closest to the actual value, thereby improving the stability and sensitivity of the following process and obtaining a better follow effect.