A fine-grained indoor passive intrusion detection method based on wlan

Abstract

The invention relates to the technical field of wireless positioning, and in particular relates to a WLAN-based fine-grained indoor passive intrusion detection method. The WLAN-based fine-grained indoor passive intrusion detection method disclosed by the invention comprises the following steps: data is transmitted by a transmitter; a signal is propagated in a monitoring area; the data is received by a receiver; the receiver transfers the received data as training data to a central server in real time firstly; the server extracts channel state information in real time; the variance of a sub-carrier amplitude variance in a sliding window is calculated and used as the signal feature, etc. According to the WLAN-based fine-grained indoor passive intrusion detection method disclosed by the invention, field data acquisition is carried out; a detection threshold value is estimated by utilization of the calculated signal feature; then, the probability whether a person exists in different windows or not can be calculated according to a hidden Markov model; finally, whether a person exists in a monitoring range can be determined; by utilization of less early training, human motion still can be detected with relatively high accuracy rate when the human motion speed is very slow; and thus, the method is suitable for indoor intrusion detection.

Description

technical field [0001] The invention relates to the technical field of wireless positioning, in particular to a WLAN-based fine-grained indoor passive intrusion detection method. Background technique [0002] With the advancement of science and technology, indoor security monitoring technology is gradually improving. There are many types of monitoring system technologies, such as video monitoring, infrared monitoring, radio frequency identification, pressure sensing and other technologies, but these technologies are used in very harsh environments. For the line-of-sight path, if there are obstacles in the middle, the performance of the monitoring system will be reduced or even failed, and the initial deployment cost of these systems is relatively high, requiring specialized infrastructure. With the development of wireless network technology in recent years, the penetration rate of wireless local area network (WLAN) is increasing rapidly, and it has a high coverage rate in de...

AI Technical Summary

Problems solved by technology

However, since CSI will be affected by the walking speed of the human body, the slower the walking speed, the smaller the impact on CSI. Therefore, the traditional method will greatly reduce the detection accuracy when the human body moves very slowly in the monitoring area.

The thief must walk very carefully when entering the room, and the walking speed may be very slow. In this case, the detection performance of the traditional method will decline.

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