Dynamic Target Acceleration Estimation Using CSI

Jiacheng Wang, Zengshan Tian, Xiaolong Yang, Mu Zhou, Jiamin Huang, Dusit Niyato

Abstract: Wireless sensing attracts significant attention in recent years, due to its ubiquitous nature, individual privacy-preserving ability, and potential for future applications, such as home security and the Internet of Things (IoT). Among the sensed information, the dynamic human target acceleration, which can be used for gait analysis and passive localization, plays an irreplaceable role. Considering the target velocity is composed of initial velocity and acceleration, this paper proposes a model to describe the relationship between the acceleration of the dynamic target and the CSI phase change between adjacent CSI packets. Based on the proposed model, the target acceleration can be estimated directly from CSI via the fractional Fourier transform, which is essentially different from the existing algorithm that derives the acceleration from target velocity. The real-world evaluation shows that the median acceleration estimation error can reach about 0.69 m/s2, verifying the effectiveness of the proposed model.