UVtrack: Multi-Modal Indoor Seamless Localization Using Ultra-Wideband Communication and Vision Sensors

Abstract

High precision and robust indoor positioning system has a broad range of applications in the area of mobile computing. Due to the advancement of image processing algorithms, the prevalence of surveillance ambient cameras shows promise for offering sub-meter accuracy localization services. The tracking performance in dynamic contexts is still unreliable for ambient camera-based methods, despite their general ability to pinpoint pedestrians in video frames at fine-grained levels. Contrarily, ultra-wideband-based technology can continuously track pedestrians, but they are frequently susceptible to the effects of non-line-of-sight (NLOS) errors on the surrounding environment. We see a chance to combine these two most viable approaches in order to get beyond the aforementioned drawbacks and return to the pedestrian localization issue from a different angle. In this article, we propose UVtrack, a localization system based on UWB and ambient cameras that achieves centimeter accuracy and improved reliability. The key innovation of UVtrack is a well-designed particle filter which adopts UWB and vision results in the weight update of the particle set, and an adaptive distance variance weighted least squares method (DVLS) to improve UWB sub-system robustness. We take UVtrack into use on common smartphones and test its effectiveness in three different situations. The results demonstrated that UVtrack attains an outstanding localization accuracy of 7 cm.

Keywords

• Visual tracking
• UWB
• indoor localization
• sensor fusion