Research On Indoor Motion Detetion And Localization Technology Based On Channel State Information

Rapid growth of communication networks and growing demands based on context-aware service have motivated significant research efforts in the area of motion detection systems. Now the activity recognition and indoor localization technology are entrenched in the lead. There are many activity recognition and indoor localization technologies at present, such as RFID, Zig Bee, camera, infrared, sensor and Wi Fi etc. Although, these techniques can provide positioning function, the aspect of practicability has more or less certain defects. Therefore, we propose a new indoor positioning technology.First of all, through comparison and analysis of existing motion detection and indoor positioning technologies we pointed out the shortcomings of existing technologies.Then through comparison and analysis the RSSI and CSI in existing motion detection and indoor positioning technologies, we point out the shortcomings of RSSI and the advantages of CSI.Second, By comparing and analyzing many experiment results, different behavior factors(such as the number and distribution of the person, the walking state, and the relative distance to the detection point etc) have different effects on detection accuracy using different WLAN information. To break the limit of human behaviors, we design and implement the Bfp, a behavior-free passive motion detection system utilizing WLAN physical layer information and MIMO technique. First, Bfp extracts its CSI information from the physical layer using the off-the-shelf device. Then we propose to extract the variance of CSI amplitude feature that is modeled to address the sensitivity to human behaviors. Moreover, to eliminate the noise effects, we employ a truncate-tale filter on the variance and then obtain its distribution profile. The Earth Mover’s Distance algorithm is utilized to distinguish the detection results. And finally, multi-streams of MIMO are leveraged to enhance the detection accuracy.Third, we design the Bfp-L indoor location system based on the Bfp motion detection technology, which need not waste much manpower to extract the offline fingerprint and maintain the fingerprint database. The positioning accuracy of our system is high and can reach 1 meters.Finally, using the computer equipped with intel 5300 wireless network card and WRVS4400 N AP, we extract the robust CSI feature. Then we emulate and evaluate the Bfp system in two typical indoor scenarios, i.e., a crowed multipath laboratory and a vacant conference hall, and the Bfp-L system in the crowed multipath laboratory.