In this thesis work, the implementations of the monopulse amplitude comparison and phase comparison DF algorithms are performed on an FPGA platform. After the mathematical formulation of the algorithms using maximum-likelihood approach is done, software simulations are carried out to validate and find the DF accuracies of the algorithms under various conditions. Then the algorithms are implemented on an FPGA platform by utilizing platform specific software tools. Block diagrams of the hardware implementations are given and explained in detail. Then simulations of hardware implementation of both algorithms are performed. Using the results of the simulations, DF accuracies under certain conditions are evaluated and compared to software simulations results.

In this thesis, the problem of Angle of Arrival estimation of radar signals with Time Difference of Arrival method in an outdoor land multipath environment with limited line of sight is analyzed. A system model is proposed. Effects of system, channel and radar parameters on the Angle of Arrival estimation performance are investigated through Monte Carlo simulations. Improving effect of utilization of diversity on the estimation performance is observed. Performances of the space diversity with noncoherent and selective combining are compared. Finally a realistic scenario is studied and performance of the proposed system is investigated.

In this thesis work, Cyclic Root MUSIC method is integrated with spatial smoothing and interpolation techniques to estimate the direction of arrivals of coherent,cyclostationary signals received via a Uniform Circular Array (UCA). Cyclic Root MUSIC and Conventional Root MUSIC algorithms are compared for various signal scenarios by computer simulations. A cyclostationary process is a random process with probabilistic parameters, such as the autocorrelation function, that vary periodically with time. Most of the man-made communication signals exhibit cyclostationarity due to the periodicity arising from their carrier frequencies, chip rates, baud rates, etc. Cyclic Root MUSIC algorithm exploits the cyclostationarity properties of signals to achieve signal selective direction of arrival estimation. Spatial smoothing is presented to overcome the coherent signals problem in a multipath propagation environment. Forward spatial smoothing and forward backward spatial smoothing techniques are investigated. Interpolation method is presented to cope with the restrictions of spatial smoothing on array structure. Although the array structure that is considered in this thesis (Uniform Circular Array), is not suitable for applying spatial smoothing directly, using interpolation method makes it possible. Performance of Cyclic Root MUSIC and Conventional Root MUSIC algorithms are compared under variation of various factors by computer simulations. Effects of signal type on the performance of the algorithms are observed by using different signal scenarios.

An important step for the design of direction finding systems is the performance evaluation using numeric electromagnetic simulation tools. In this thesis, a method is presented for both modeling and simulation in a numeric electromagnetic simulation tool FEKO. The method relies on the data generated by FEKO. The data is then processed by correlative interferometer algorithm. This process is implemented in a MATLAB environment. Different types of antenna arrays including dipole, monopole and discone antennas are used. The antenna arrays are mounted on a UAV and SUV in order to see the platform effects. The direction finding performance is evaluated for different scenarios. It is shown that the presented approach is an effective tool for understanding the direction finding characteristic of antenna arrays.

Ground based radars often experience difficulties in target detection and direction finding (DF) applications due to the interference between the direct and surface reflected signals when the targets fly at low altitudes. In this thesis, the phenomena governing the low angle propagation are overviewed and a multipath signal model including the effects of refraction, specular reflection, diffuse reflection, curvature of the earth and antenna polarization is presented. Then, the model is utilized to develop detection and DF algorithms for the targets at low altitudes. The target detection algorithm aims to increase signal-to-noise ratio (SNR) to overcome the effects of signal fading caused by surface reflections. The algorithm is based on diversity combining and the combining weight vector is calculated by maximizing average value of SNR. The technique is compared with Maximum Ratio Combining (MRC) algorithm which is optimal in terms of SNR. In direction finding, it is the height of the target that is explored since the target range information is obtained from the time delay. The target height is estimated by utilizing Maximum Likelihood Estimation (MLE). The performance of our algorithm is compared with that of the technique that is known in the literature as Refined Maximum Likelihood (RML).

In this thesis, optimization of the geometry of non-uniform arrays for direction finding yielding unambiguous results is studied. A measure of similarity between the array response vectors is defined. In this measure, the effects of antenna array geometry, source placements and antenna gains are included as variable parameters. Then, assuming that the antenna gains are known and constant, constraints on the similarity function are developed and described to result in unambiguous configurations and maximum resolution. The problem stated is solved with two different methods, the MATLAB optimization toolbox, and genetic algorithm in which different genetic codings are also studied. The performance of the MUSIC algorithm with the optimized array geometries are investigated through computer simulations. The direction of arrival estimates are obtained using the optimized array geometry on the MUSIC algorithm along with the effects of different parameters. Statistics of the true and probable erroneous arrival angles and the probability of gross error are obtained as a measure of performance. It is observed that the proposed optimization process for the array geometry gave rise to unambiguous results for direction finding.

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<p dir="ltr">Accurately locating a radio-frequency (RF) emitter is imperative in the defense sector, and passive direction finding systems are intriguing due to relatively low cost. This approach involves using the time difference between a signal’s impact at equispaced antennas to determine the location of the emitter, a particular challenge for wideband waveforms operating near the noise floor. Microwave photonic systems have been demonstrated for passive direction finding. These techniques possessed drawbacks, such as reliance on the incoming signal’s bandwidth, dependence on laser power, or the inability to recover an angle from wideband pulses. This thesis presents a novel approach to passive direction finding by translating the methods of spectral interferometry from the optical domain to RF. Spectral interferometry involves interfering a time-delayed reference pulse with a “signal” pulse that has passed through an unknown system. By removing the spectral phase of the reference pulse from the resulting interferogram, the spectral phase of the uncharacterized system is recovered. This enables direction-finding for many waveforms, including the wideband low peak power chirps frequently used in radar. Incorporating an analog optical delay line into both a hard-wired RF interferometer and a two-element antenna array demonstrated spectral interferometric processing of chirped signals with up to 1 GHz instantaneous bandwidth. The technique extracted accurate delays and angles to within 2$\degree$ throughout testing. This approach only requires the imposed delay be longer than the autocorrelation of the bandwidth limited pulses. With additional backend processing, this method could simultaneously determine the angle and classify the incoming signal.</p>

Source localization with a wireless sensor network remains an important area of research as the number of applications with this problem increases. This work considers the problem of source localization by a network of passive wireless sensors. The primary means by which localization is achieved is through direction-finding at each sensor, and in some cases, range estimation as well. Both single and multiple-target scenarios are considered in this research. In single-source environments, a solution that outperforms the classic least squared error estimation technique by combining direction and range estimates to perform localization is presented. In multiple-source environments, two solutions to the complex data association problem are addressed. The first proposed technique offers a less complex solution to the data association problem than a brute-force approach at the expense of some degradation in performance. For the second technique, the process of signal classification is considered as another approach to the data association problem. Environments in which each signal possesses unique features can be exploited to separate signals at each sensor by their characteristics, which mitigates the complexity of the data association problem and in many cases improves the accuracy of the localization. Two approaches to signal-selective localization are considered in this work. The first is based on the well-known cyclic MUSIC algorithm, and the second combines beamforming and modulation classification. Finally, the implementation of a direction-finding system is discussed. This system includes a uniform circular array as a radio frequency front end and the universal software radio peripheral as a data processor. / Master of Science

A radio direction finding (DF) system is an antenna array and a receiver arranged in a combination to determine the azimuth angle of a distant emitter. Basically, all DF systems derive the emitter location from an initial determination of the angle-of-arrival (AOA). Radio direction finding techniques have classically been based on multiple-antenna systems employing multiple receivers. Classic techniques such as MUSIC [1][2] and ESPRIT use simultaneous phase information from each antenna to estimate the angle-of-arrival of the signal of interest. In many scenarios (e.g., hand-held systems), however, multiple receivers are impractical. Thus, single channel techniques are of interest, particularly in mobile scenarios. Although the amount of existing research for single channel DF is considerably less than for multi-channel direction finding, single channel direction finding techniques have been previously investigated. Since many of the single channel direction finding techniques are older analog techniques and have been analyzed in previous work, we will investigate a new single channel direction finding technique that takes specific advantage of digital capabilities. Specifically, we propose a phase-based method that uses a bank of Phase-Locked Loops (PLLs) in combination with an eight-element circular array. Our method is similar to the Pseudo-Doppler method in that it samples antennas in a circular array using a commutative switch. In the proposed approach the sampled data is fed to a bank of PLLs which track the phase on each element. The parallel PLLs are implemented in software and their outputs are fed to a signal processing block that estimates the AOA. This thesis presents the details of the new Phase-Locked Loop (PLL) algorithm and compares its performance to existing single channel DF techniques such as the Watson-Watt and the Pseudo-Doppler techniques. We also describe the implementation of the PLL algorithm on a DRS Signal Solutions, Incorporated (DRS-SS) WJ-8629A Software Definable Receiver with Sunrise™ Technology and present measured performance results. / Master of Science