Signal Recognition for Wireless Sensing Application

Abstract

Until now, wireless recognition has already built a giant system and adopted everywhere. In medical treatment, geography detects high accurate machine examination. Or some daily applications like fingerprint recognition and handwriting recognition and face recognition, all these technologies are making our lives better. It became necessary to modern science development now. With the development of technology and widely used of wireless recognition, the requirement of accuracy and safety is continually increasing. To avoid being influenced by white noise and signal from other devices, the process of doing wireless signal modulation, translation, conversion and recognition method is much completely than before. Sometimes it too hard to let the user comprehend and analyses the signal, or there a big amount of data, in this case, we can let the computer do it by itself. That’s what we called machine learning. With the technic of machine learning, a computer can recognize by itself, moreover, it’s able to do the prediction of the data. In this project, I’m going to use radar to do a wireless signal recognition application experiment by setting several different scenes and do the measurement by the radar. And adapt the measurement result into the convolution neural network, and research that if the convolutional neural network is able to learn the data and recognize other data scans from the same scene. The research can help us to find that if neural network deep learning can be used in signal recognition, which can be applicated in radar security detective, geography radar detective issue, etc.