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Academic Journal of Computing & Information Science, 2021, 4(7); doi: 10.25236/AJCIS.2021.040709.

Human Positioning System based on Pyroelectric Infrared Sensor and GA-BP Neural Network

Author(s)

Xuneng Tong, Wufeng Wang, Zhigang Han

Corresponding Author:
Zhigang Han
Affiliation(s)

Integrated Circuit Engineering Department, Tongji University, Shanghai, China

Abstract

In order to use the PIR sensor to position the human body more effectively, this article proposes a human target positioning system based on multiple sensors layouts and GA-BP neural network. On the hardware, an PIR peripheral circuit is designed to detect, amplify, and filter infrared signals. On the software, this article uses genetic algorithm to optimize BP neural network, and designs a trilateration algorithm to convert the distances from the three sensors to  human into coordinates. The experimental results show that the GA-BP neural network converges faster, the mean square error of the X-axis and Y-axis are reduced by 90.3% and 81.9%, and the positioning error is reduced by 0.24m.

Keywords

PIR, Human target positioning, amplifying and filtering circuit, GA-BP neural network, trilateration

Cite This Paper

Xuneng Tong, Wufeng Wang, Zhigang Han. Human Positioning System based on Pyroelectric Infrared Sensor and GA-BP Neural Network. Academic Journal of Computing & Information Science (2021), Vol. 4, Issue 7: 59-66. https://doi.org/10.25236/AJCIS.2021.040709.

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