1. An Enhanced Radio Tomographic Imaging Localization Method Based on Low-cost Wireless Sensor Networks
- Author
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Wei Ke, Jie Jin, Jun Lu, Haoran Zuo, Mengling Chen, and Yanli Wang
- Subjects
Brightness ,Tomographic reconstruction ,Pixel ,business.industry ,Computer science ,020302 automobile design & engineering ,020206 networking & telecommunications ,02 engineering and technology ,Interference (wave propagation) ,0203 mechanical engineering ,Position (vector) ,Feature (computer vision) ,0202 electrical engineering, electronic engineering, information engineering ,Computer vision ,Artificial intelligence ,business ,Device free localization ,Wireless sensor network - Abstract
As one of the main methods of device free localization (DFL) that can locate a target without attaching any devices, the radio tomographic imaging (RTI) method based on the low-cost wireless sensor network (WSN) has wide application prospects. The current RTI positioning methods mainly determine a target position by searching the maximum brightness pixel in a RTI map. However, due to the existence of environmental noises and interference, the brightness of the pseudo-target is often greater than that of the real target, resulting in a misjudgment of the target and even a great positioning error. In this paper, an enhanced RTI (E-RTI) positioning method that combines target shape features with the target brightness feature is proposed for overcoming this problem. This method can effectively reduce the negative influence of pseudo-targets and environmental noises by using the target shape prior information. The experimental results show that the positioning accuracy of this method is better than the existing RTI method.
- Published
- 2019
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