Imaging using Phase Coded Complimentary Code Pairs

This paper clearly demonstrates and estimates the humans present in the room through the wall. Compared to the Wi-Fi signals, less harm to the human beings of RF signal is sent from the transmitter, hence they are traveled through the walls and reflect from the objects like human beings. We apply the Neural Network concepts approach to analyze those signals for the detection of objects. We have analyzed the transmitted RF signals and received RF signals in the receiver, and this stored data is also used to find the objects randomly placed in the room. The proposed method is used neural networks and uses an 80–20 train-test split for reconstruction and classification. For this purpose, we have developed a 2-D radar system that requires one transmitting Antenna and many receivers. Transmitter uses pulse type of signals are transmitted and with a frequency of 3 GHz so that this signal with that frequency can travel through the wall with less attenuation. Demodulated signals are processed and extract the spatial features, predict the number of people present in the room, and aggregate information over many time steps respectively. Mainly it focuses on the receiver design to avoid the reflection from the stationary objects and track the date of motion of a human body with the help of an antenna array with a narrow RF beam The target was detected 44 times out of 46 leading to missed detection of about 4.35%. False detection was zero. Objectives of the papers are: after demodulated signals are analyzed so that they can give the e shape of the object, location of object and type of the object whether it is moving or stationary and gives the material properties of the object.