GSM based Communication-Sensor (CommSense) System - Bhatta, Abhishek (Department of Electrical Engineering, 2018)
Using communication signals for radar applications has been a major area of research in radar engineering. In the recent years, due to the widely available wireless signals, a new area of research called commensal radars has emerged. Commensal radars use available wireless Radio Frequency (RF) signals to detect and track targets of interest. This is achieved by placing two antennas, one towards the transmitting base station and the other towards the surveillance area. The signal received by these two antennas are correlated to determine the location and velocity of the target. When a signal passes through a channel, it reflects off the obstacles within its path. These reflections usually degrade quality of the signal and cause interference to the telecommunication systems. To mitigate the effects of the channel on a signal these systems transmit a known bit sequence within each frame. Our goal, with this thesis, is to design and implement a working prototype of a novel architecture for the commensal radar system, which uses these known bit sequences to extract the channel information and determine events of interest. The major novelties of the system are as follows. Firstly, this system will be built upon existing communication systems using Software Defined Radio (SDR) technology. Secondly, this design eliminates the need for a reference antenna, which reduces the cost of the system and creates an opportunity to make the system portable. We name this system Communication-Sensing (CommSense). Since, our plan is to use Global System for Mobile Communication (GSM) as the parent system for the prototype development, we decide to update the name to GSM based Communication-Sensing (GSM-CommSense) system. This thesis begins with theoretical analysis of the feasibility of the GSM-CommSense system. First of all, we perform a link budget analysis to determine the power requirements for the system. Then we calculate the ambiguity function and Cram´er-Rao Lower Bound (CRLB) for a two-path received signal model. With encouraging theoretical results, we design a prototype of the system that can capture real GSM base station broadcast signals. After the design of the GSMCommSense system, we capture channel data from multiple locations with varying environmental conditions. The aim for this set of experiment is to be able to distinguish between different environmental conditions. Then, we performed statistical analysis on the data by means of Probability Density Function (PDF) fitting, a goodness-of-fit test called chi-square test and a clustering algorithm called Principal Components Analysis (PCA). We have presented the results from each analysis and discussed them in detail. Upon, receiving positive results in each step we have decided to move towards using learning algorithms to categorise the data captured by the system. We have compared two widely accepted supervised learning algorithms, called Support Vector Machines (SVM) and Multi-Layer Perceptron (MLP). The results showed that with the current hardware capabilities of the system and the amount of data available per GSM frame, the performance of SVM is better than MLP. Thus, we have used SVM to classify two events of detection and classification across a wall. We have presented our findings and discussed the results in detail. We conclude our current work and provide scope for future work in development and analysis of the GSM-CommSense system.