This paper, Through-wall Human Pose Estimation Using Radio Signals, is extracted from a paper in CVPR2018 published by Dina Katabi, a famous team in the wireless communication field, and demonstrates accurate human pose estimation through walls and occlusions.
In this paper, the system RF-pose designed by wireless signals can accurately predict human activities, and it also has very accurate prediction results when the environment is blocked by walls and other obstacles.
The paper named Precise Power Delay Profiling with Commodity Wi-Fi is written by Yaxiong Xie, Mo Li`s student in Nayang Technological University. This note is a recap in a easy-to-understand manner.
The presence of reflectors in the environment surrounding a transmitter and receiver create multiple paths that a transmitted signal can traverse.
As a result, the receiver sees the superposition of multiple copies of the transmitted signal, each traversing a different path. Each signal copy will experience differences in attenuation, delay and phase shift while travelling from the source to the receiver. This can result in either constructive or destructive interference, amplifying or attenuating the signal power seen at the receiver. Strong destructive interference is frequently referred to as a deep fade and may result in temporary failure of communication due to a severe drop in the channel signal-to-noise ratio.
These instructions are currently expected to work on Linux operating systems that are based on an upstream Linux kernel version between 3.2 (e.g. Ubuntu 12.04) and 4.2 (e.g. Ubuntu 14.04.4).
The IWL5300 provides 802.11n channel state information in a format that reports the channel matrices for 30 subcarrier groups, which is about one group for every 2 subcarriers at 20 MHz or one in 4 at 40 MHz. Each channel matrix entry is a complex number, with signed 8-bit resolution each for the real and imaginary parts. It specifies the gain and phase of the signal path between a single transmit-receive antenna pair.
