An indoor human motion detection algorithm based on channel state information

Human motion detection based on CSI (Channel State Information) is a hot research topic. Many researchers started to focus on it. By extracting amplitude and phase of CSI, it can be applied to detect human motions. In this paper, we employ the phase to detect intrusion. Firstly, we use a liner transformation to eliminate the shift of phases of different subcarriers. Subsequently, we defined two reference points for the short-term case(SES) and the long-term case(LES). The former is used to detect if someone is walking in indoor room and the latter is to detect whether the person is walking continuously. We implemented our approaches with the normal WiFi equipment and evaluated the performances of our algorithm in real environment. Experimental results show a high accuracy of our algorithm.