Radio Frequency Direction of Arrival Determination

1. Radio Frequency Direction of Arrival Determination Daniel Lazar, Jichuan Li, Ed Richter, and AryeNehorai Department of Electrical and Systems Engineering Abstract Data Acquisition Results In this project, I implement and test direction of arrival algorithms to find the angle of arrival of transmitted radio frequency signals relative to an array of receivers. A specific emphasis is put on creating a convenient, reliable tool that measures angle of arrival in real time. This project also finds a proper experimental setup required to achieve reliable results. The MuSIC (multiple signal classification) algorithm is used, as well as a variant, smooth-MuSIC, which does not assume uncorrelated signals, and so mitigates the effects of multipath interference. Beamforming techniques, which combine temporal and spatial filtering, are also used to find the direction of arrival. Further work building on this research can find direction of arrival in 3 dimensions, or change array spacing to determine the direction of arrival of a greater number of signals. This versatile platform can be used to investigate many issues relevant to communication systems. • Designed Labview VI to show angle-of-arrival spectrum • Can support a variable number of transmitters and receivers • Calculates angle of arrival in real time • Use carrier frequency 440MHz • To prevent spatial aliasing, keep receivers with half a wavelength, or 34cm, of each other • Far field assumption • Gigabit ethernet cables transmit data to laptop • Use 10MHz frequency reference for transmitter and receivers • Incoming signals must be aligned at the start of every session due to constant random phase delay between receiver signals Experimental setup with 5 receivers and transmitter at 75 degrees Experimental Setup Goal: To implement source location algorithms that use data from an array of receivers to discern the location of the source. Received signals DOA Spectra, transmitter at 75 degrees with 5 receivers After implementing MuSIC and beamforming, both algorithms worked effectively after great efforts to minimize multipath interference. In the presence of sever multipath, MuSIC slightly outperformed beamforming. Smooth-MuSIC showed promise in multipath situations, but there was not enough time to fully test it. There is much room for continued investigation. Smooth-MuSIC must be fully tested, and there are many other algorithms to implement, each with their own advantages. After their implementation, a more rigorous test environment will allow us to determine in which situations to use each algorithm. Additionally, we can run this using multiple signal sources and determine how close transmitters can be while the algorithms can discern two separate sources. This mobile testing platform will be a jumping off point for further work. Signals on an array of 3 receivers, with transmitter at 30 degrees Overview When a transmitted signal hits an array of receivers at an angle, there is a time delay between when the signal hits each receiver. If there if only one signal and there is not much noise, correlation can be used to find the direction of arrival. However, if there are multiple signals, noise, or interfering signals, then more sophisticated algorithms must be used to estimate angle of arrival of each signal. Of particular concern in a small testing environment is multipath interference,which results from a signal bouncing off of an object and then hitting the receiver. This appears as a second identical signal with a time delay. If one uses certain frequencies, great care must be taken to address that issue. Using a 440 MHz carrier frequency posed severe multipath issues. Radio units must be several meters from walls, objects, or people to minimize self-interference. References and Acknowledgments Thanks to Ed Richter for spending countless hours on this project, Jichuan Li for assisting with the theoretical background, Prateek Vijay for his involvement, and Professor Nehorai for making this possible. 1.Nehorai, A. Lecture slides from CSSIP Lab. 2,3.Professor RavirajAdve’s notes: http://www.comm.utoronto.ca/~rsadve