Wi-Fi Radar System 2.0 is a scientific research and teaching platform for wireless sensing that includes signal analysis and human motion detection. Signal analysis module can help researchers and students to collect, observe and record wireless signal features (CSI and RSSI) in real time so as to find the factors that affect the signal variation and inspire innovative research and applications. As a typical application of wireless sensing, human motion detection can help students understand and learn the application of WiFi radar technology and inspire their innovative thinking.
Figure 1. Wi-Fi Radar System Interface
Wi-Fi radar system consists of back-end program (data generation and transmission) and the front-end program (data display and collection). The back-end program needs to run on a microcomputer equipped with a transmitting antenna. The front-end program needs to run on any device that support java environment and be installed in the same local area network. Below is entire process of starting this system.
Figure 2. System executing command
$java -jar VisualCSI.jar
The real-time visualization system of WiFi radar data can be divided into two parts:
1. Real-time management of signal features
2. Human detection alarms
Figure 4. Wi-Fi Radar System Interface
Figure 5. The interface of connecting successfully
Figure 6. Display of signal features
Click on each of the widgets in Box 2 and signal information will show in the highlighted area of Box 3 (as shown in Figure 7). Users can observe the changes of each sub-carrier or signal features more clearly .
Figure 7. Display of signal amplification
Figure 8. Frequency regulation area
Human detection functions include alarm indication area and selection of detection parameters.
Functions described in 3.2 and 3.3 can enable users to observe changes of signal features in real time and help them make intuitive and qualitative analysis of feature changing.
The system integrates two human detection algorithms. One is based on signal amplitude variance and the other is based on amplitude average.
We use human detection and localization as a typical example to help teachers and students understand the use of WiFi radar system. Human detection could be used in security systems. This example is only used to demonstrate how to use this system to realize simple human detection. Because the demo algorithm is too simple, there is room for improvement in both accuracy and robustness. Users should design algorithms based on CSI data provided by the system to achieve specific purpose.
After original data is collected, it needs to be processed into the format required by the experiment. In this experiment, we need to extract the amplitude and phase of the signals from the CSI in the complex form as eigenvalue of the CSI data.
In order to observe the signal changes in the time domain, WiFi radar uses the amplitude and variance information to determine the stability of the surrounding environment in order to detect human motion. After completing the data processing, the WiFi radar stores the carrier amplitude of the data packet in a buffer (time window). The buffer is set to hold information of 30 packets. Carrier amplitude information in the buffer can be represented by a 30 by 30 matrix, as shown in Figure 12.
Above is design and implementation process of human motion detection algorithm based on the amplitude and variance of WiFi Radar. We believe teachers and students can think out more innovative human detection algorithms referring to above analysis.
All the password of the system is 123456