With the expansion of unmanned aircraft system (UAS) technologies, there is a growing need for UAS Traffic Management (UTM) systems to promote safe operation and development. To be successful, these UTM systems must be able to detect and track multiple drones in the presence of clutter. This paper examines the implementation of different algorithms on a compact, X-band, frequency modulated continuous wave (FMCW) radar in an effort to enable more accurate detection and estimation of drones. Several algorithms were tested through post processing on actual radar data to determine their accuracy and usefulness for this system. A promising result was achieved through the application of pulse-Doppler processing. Post processing on recorded radar data showed that a moving target indicator successfully separated a target from clutter. An improvement was also noted for the implementation of phase comparison monopulse which accurately estimated angle of arrival (AOA) and required fewer computations than digital beamforming.The second part of this thesis explains the work done on an adaptive broadband, real time beamformer for RF interference (RFI) mitigation. An effective communication system is reliable and can counteract the effects of jamming. Beamforming is an appropriate solution to RFI. To assist in this process FPGA firmware was developed to prepare signals for frequency domain beamforming. This system allows beamforming to be applied to 150 MHz of bandwidth. Future implementation will allow for signal reconstruction after beamforming and demodulation of a communication signal.

In accommodating the growing global demand for wireless, Multi-User Multiple-Input and Multiple-Output (MU-MIMO) systems have been identified as the key technology. In such systems, a transmitting basestation serves several users simultaneously, increasing the network capacity. However, sharing the same time-frequency physical resources can cause interference for the simultaneously scheduled users if not moderated properly. One way to mitigate this interference is by directing radio power through the radio channel in specific directions, a method which is called beamforming. Following the successful implementation of the AlphaZero algorithm in another radio resource management technique, scheduling, this thesis explores the potential of using a similar search-based method for the beamforming problem, striving towards the ultimate objective of making decisions for scheduling and beamforming jointly. However, as AlphaZero only supports discrete action spaces and the action space of the beamforming problem is continuous, a modification of the algorithm is required. The proposed course of action is to extend AlphaZero into Sampled AlphaZero, using sample-based policy improvement to create an algorithm that is both more scalable for large discrete action spaces and able to handle high dimensional continuous action spaces. To evaluate the performance of the models, test environments were simulated and solved using increasingly larger so-called codebooks, containing predefined beamforming solutions. The results of the Sampled AlphaZero model demonstrated promising performance even for very large codebook sizes, indicating the model's suitability for addressing the beamforming problem in a non-codebook-based context. Furthermore, this thesis explores how states in the search can be represented and preprocessed for the neural network to learn efficiently, demonstrating clear benefits of using a singular value decomposition-based state preprocessing over raw states as input to the neural network.

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Radar systems vary significantly in size, weight, power, and cost (SWaP-C) characteristics with many high SWaP-C models being inaccessible to consumers. Recognizing this, we have engineered an effective but low SWaP-C networked radar system tailored for detecting and tracking unmanned air vehicle (UAV) traffic. Using field-programmable gate arrays (FPGAs), and custom-designed printed circuit boards (PCBs), our system achieves remarkable efficiency without compromising performance. We use patch antennas for our transmitter and in our 4x4 receiver array. With our low SWaP-C system we have successfully concluded outdoor range testing, detecting corner reflector targets at a remarkable 10dB above our noise floor up to a distance of 100m. We have also finished testing and implementation of our angle of arrival (AOA) algorithm, using conjugate field matched (CFM) beamforming, with outdoor testing using both corner reflectors and drones. Combining our range and AOA algorithms we have detected and tracked both a corner reflector and a drone through time and created a 3D plot showing our target's path and location relative to our system. With this we have demonstrated the viability and effectiveness of our low SWaP-C radar for UAV traffic surveillance.

The capacity of a cellular system is limited by two different phenomena, namely multipath fading and multiple access interference (MAI). A Two Dimensional (2-D) receiver combats both of these by processing the signal both in the spatial and temporal domain. An ideal 2-D receiver would perform joint space-time processing, but at the price of high computational complexity. In this dissertation we investigate computationally simpler technique termed as a Beamformer-Rake. In a Beamformer-Rake, the output of a beamformer is fed into a succeeding temporal processor to take advantage of both the beamformer and Rake receiver. Wireless service providers throughout the world are working to introduce the third generation (3G) cellular service that will provide higher data rates and better spectral efficiency. Wideband CDMA (WCDMA) has been widely accepted as one of the air interfaces for 3G. A Beamformer-Rake receiver can be an effective solution to provide the receivers enhanced capabilities needed to achieve the required performance of a WCDMA system. This dissertation investigates different Beamformer-Rake receiver structures suitable for the WCDMA system and compares their performance under different operating conditions. This work develops Beamformer-Rake receivers for WCDMA uplink that employ Eigen-Beamforming techniques based on the Maximum Signal to Noise Ratio (MSNR) and Maximum Signal to Interference and Noise Ratio (MSINR) criteria. Both the structures employ Maximal Ratio Combining (MRC) to exploit temporal diversity. MSNR based Eigen-Beamforming leads to a Simple Eigenvalue problem (SE). This work investigates several algorithms that can be employed to solve the SE and compare the algorithms in terms of their computational complexity and their performance. MSINR based Eigen-Beamforming results in a Generalized Eigenvalue problem (GE). The dissertation describes several techniques to form the GE and algorithms to solve it. We propose a new low-complexity algorithm, termed as the Adaptive Matrix Inversion (AMI), to solve the GE. We compare the performance of the AMI to other existing algorithms. Comparison between different techniques to form the GE is also compared. The MSINR based beamforming is demonstrated to be superior to the MSNR based beamforming in the presence of strong interference. There are Pilot Symbol Assisted (PSA) beamforming techniques that exploit the Minimum Mean Squared Error (MMSE) criterion. We compare the MSINR based Beamformer-Rake with the same that utilizes Direct Matrix Inversion (DMI) to perform MMSE based beamforming in terms of Bit Error Rate (BER). In a wireless system where the number of co-channel interferers is larger than the number of elements of a practical antenna array, we can not perform explicit null-steering. As a result the advantage of beamforming is partially lost. In this scenario it is better to attain diversity gain at the cost of spatial aliasing. We demonstrate this with the aid of simulation. Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier technique that has recently received considerable attention for high speed wireless communication. OFDM has been accepted as the standard for Digital Audio Broadcast (DAB) and Digital Video Broadcast (DVB) in Europe. It has also been established as one of the modulation formats for the IEEE 802.11a wireless LAN standard. OFDM has emerged as one of the primary candidates for the Fourth Generation (4G) wireless communication systems and high speed ad hoc wireless networks. We propose a simple pilot symbol assisted frequency domain beamforming technique for OFDM receiver and demonstrate the concept of sub-band beamforming. Vector channel models measured with the MPRG Viper test-bed is also employed to investigate the performance of the beamforming scheme. / Ph. D.

The detection and localization of important acoustic events in a complex urban environment, such as gunfire and explosions, is critical to providing effective surveillance of military and civilian areas and installations. In a complex environment, obstacles such as terrain or buildings introduce multipath propagations, reflections, and diffractions which make source localization challenging. This dissertation focuses on the problem of source localization in three-dimensional (3D) realistic urban environments. Two different localization techniques are developed to solve this problem: a) Beamforming using a few microphone phased arrays in conjunction with a high fidelity model and b) Fingerprinting using many dispersed microphones in conjunction with a low fidelity model of the environment. For an effective source localization technique using microphone phased arrays, several candidate beamformers are investigated using 2D and corresponding 3D numerical models. Among them, the most promising beamformers are chosen for further investigation using 3D large models. For realistic validation, localization error of the beamformers is analyzed for different levels of uncorrelated noise in the environment. Multiple-array processing is also considered to improve the overall localization performance. The sensitivity of the beamformers to uncertainties that cannot be easily accounted for (e.g. temperature gradient and unmodeled object) is then investigated. It is observed that evaluation in 3D models is critical to assess correctly the potential of the localization technique. The enhanced minimum variance distortionless response (EMVDR) is identified to be the only beamformer that has super-directivity property (i.e. accurate localization capability) and still robust to uncorrelated noise in the environment. It is also demonstrated that the detrimental effect of uncertainties in the modeling of the environment can be alleviated by incoherent multiple arrays. For efficient source localization technique using dispersed microphones in the environment, acoustic fingerprinting in conjunction with a diffused-based energy model is developed as an alternative to the beamforming technique. This approach is much simpler requiring only microphones rather than arrays. Moreover, it does not require an accurate modeling of the acoustic environment. The approach is validated using the 3D large models. The relationship between the localization accuracy and the number of dispersed microphones is investigated. The effect of the accuracy of the model is also addressed. The results show a progressive improvement in the source localization capabilities as the number of microphones increases. Moreover, it is shown that the fingerprints do not need to be very accurate for successful localization if enough microphones are dispersed in the environment. / Ph. D.