A Training-Free Method for Suppressing Radio Tomographic Imaging Artifacts in UWB Systems

With the rapid development in the field of the Internet of Things (IoT), location information of people has become an indispensable part of achieving intelligent and digital management. Ultra-wideband (UWB) technology is widely used in indoor active positioning due to the characteristics of its pulse signals, which can achieve high-precision positioning within a range of a few centimeters. However, in device-free localization (DFL), the UWB tomography localization technique is highly disturbed by artifacts and requires a priori information about the number of known people to solve for the location of the target. In order to overcome this challenge, a training-free method is proposed in this paper to suppress radio tomographic imaging (RTI) artifacts in UWB systems. This method uses a single anchor L-shaped movement (LSM) to optimize the link layout and utilizes an improved elliptical model for precise linkpixel mapping. Finally, image reconstruction is achieved through guided filtering technology, effectively suppressing artifact interference. Experiments show that the method can achieve high-accuracy localization of multiple targets based on unknown a priori information about the number of people using received signal strength (RSS). When the number of positioning targets is 4, the quantity detection accuracy can reach 97%, and the system positioning error is less than 0.19 m.