Radio Frequency Emitter Geolocation Using Cubesats

The ability to locate an RF transmitter is a topic of growing interest for civilian and military users alike. Geolocation can provide critical information for the intelligence community, search and rescue operators, and the warfighter. The technology required for geolocation has steadily improved over the past several decades, allowing better performance at longer baseline distances between transmitter and receiver. The expansion of geolocation missions from aircraft to spacecraft has necessitated research into how emerging geolocation methods perform as baseline distances are increased beyond what was previously considered. The CubeSat architecture is a relatively new satellite form which could enable small-scale, low-cost solutions to USAF geolocation needs. This research proposes to use CubeSats as a vehicle to perform geolocation missions in the space domain. The CubeSat form factor considered is a 6-unit architecture that allows for 6000 cm3 of space for hardware. There are a number of methods which have been developed for geolocation applications. This research compares four methods with various sensor configurations and signal properties. The four methods\u27 performance are assessed by simulating and modeling the environment, signals, and geolocation algorithms using MATLAB. The simulations created and run in this research show that the angle of arrival method outperforms the instantaneous received frequency method, especially at higher SNR values. These two methods are possible for single and dual satellite architectures. When three or more satellites are available, the direct position determination method outperforms the three other considered methods

Kinematic and cyclostationary parameter estimation for co-channel emitter location applications

The problem of locating a signal source, or an emitter, has many civilian and military applications, such as communication regulations enforcement, military reconnaissance, and search-and-rescue operations. Many of the most widely used emitter location methods rely on the accurate and robust estimation of the differential time delay, or time-difference-of-arrival (TDOA), and the differential Doppler shift, or frequency- difference-of-arrival (FDOA), between signal replicas arriving at two spatially separated receivers. There are many conventional methods for estimating TDOA and/or FDOA. However, these methods are unable to produce unbiased TDOA and FDOA estimates when multiple emitters are located spatially close to each other. In many cases, the spatial proximity at which the conventional methods fail is still unacceptably large for precision emitter location applications. This problem is made even more diffcult when separating signals from multiple emitters that share the same regions of the spectrum at the same time. When spatially close emitters overlap spectrally and temporally, robust TDOA and FDOA estimation is diffcult, and accurate emitter location not only requires both estimation of TDOA, or FDOA, or both jointly, but also the estimation of a signal parameter that can be used to separate the signal-of-interest (SOI) from a signal(s)-not-of-interest (SNOI) that are both within the receiver's field of view. The signal separation pa- rameter selected depends on the type of signal modulation. In this thesis, the signals of interest are bauded signals. The separation methodology for such signals is cyclo- stationarity with parameterization by cyclic frequency. Based on this assumption, a new three-dimensional joint estimation method for TDOA, FDOA, and cyclic frequency parameters, called alpha cross ambiguity function (alpha-CAF), has been developed to ex- ploit signal modulations with cyclostationary properties. By exploiting cyclostationarity, alppha-CAF can produce separate unbiased TDOA and FDOA estimates that will in turn yield reliable geolocation estimates for precision emitter location applications even when severe interference causes conventional methods to fail. In this thesis the alpha-CAF param- eter estimation (TDOA, FDOA, Cyclic Frequency) algorithm is introduced along with a complete analysis of its performance compared to conventional estimators. A connection is also made between the alpha-CAF algorithm and the additional steps needed to perform an emitter location technique

Distributed Passive Sensor Network for the Geolocation of RF Emitters

The ability to localize an RF emitter has emerged in both commercial and military technology, and is an important capability in modern cognitive radios to achieve spectral awareness. Of importance, is the accuracy of the geolocation of the RF emitter. In this thesis, we address the blind localization problem given a network of software-defined radio receivers that monitor the spectrum to determine the presence of an unknown emitter. We discuss the underlying challenges and various approaches to the geolocation problem that can be utilized. In particular, two algorithms that are used extensively in literature are investigated: time-difference of arrival, and power-difference of arrival. In the first part of the thesis, the algorithms are presented, and the error performance is characterized analytically, and then conducted through simulation. A more robust method which implements the fusion of both algorithms for an improved estimation. In the second part, we conduct a small- scale laboratory emulation of the geolocation algorithms on a network of radios to contrast the simulation results of the algorithms from the emulation results. The results provided insight to the shortcomings of each algorithm, and potential extensions for further accuracy improvement

Performance analysis and enhancements for the music sub-space direction-finding algorithm in the presence of wideband signals

Includes supplementary materialThe collection of signals intelligence via passive direction finding and geolocation of radio frequency signals is of great concern to the military for its contribution to the development of battlespace awareness. Basic subspace direction finding techniques provide a method of determining the direction-of-arrival (DOA) of multiple signals on an array of receivers, but they have an inherent limitation in that they are narrowband by design. The impact of various signal frequencies, bandwidths, and signal to noise ratios present in the source signals received by a sparse array using the multiple signals classification (MUSIC) subspace direction-finding algorithm are evaluated in this thesis. Additionally, two performance enhancements are presented: one that reduces the MUSIC computational load and one that provides a method of utilizing collector motion to resolve DOA ambiguities.http://archive.org/details/performancenalys1094544676Lieutenant Commander, United States NavyApproved for public release; distribution is unlimited

Direction Finding With Mutually Orthogonal Antennas

Estimating the direction-of-arrival of incident electromagnetic plane waves (a.k.a. direction finding or DF) has typically been accomplished in the past using arrays of spatially separated antennas. The spatial separation produces a delay in each antenna\u27s measured voltage due to the finite propagation time as the wave strikes each antenna in succession. In this thesis, we approach the problem differently by using three antennas that have been oriented in orthogonal directions but are co-located at the origin of a coordinate system. Being co-located, this mutually orthogonal arrangement of antennas cannot detect the propagation phase delay and must rely solely on the polarization properties of the incident waves. Using the vector effective height concept, three algorithms are formulated. The first algorithm estimates the direction-of-arrival by computing a vector that is perpendicular to the locus of the instantaneous electric field vector. The second and third algorithms are based on the well-known maximum likelihood and MUSIC algorithms. Simulation results show that each algorithm can estimate the direction-of-arrival with a root-mean-squared error within 1° or less when the incident wave is circularly polarized, the antennas are small compared to wavelength, and the signal-to-noise ratio is above 20dB

An Analysis of Radio-Frequency Geolocation Techniques for Satellite Systems Design

This research 1) evaluates the effectiveness of CubeSat radio-frequency geolocation and 2) analyzes the sensitivity of different RF algorithms to system parameters. A MATLAB simulation is developed to assess geolocation accuracy for variable system designs and techniques (AOA, TDOA, T/FDOA). An unconstrained maximum likelihood estimator (MLE) and three different digital elevation models (DEM) are utilized as the surface of the Earth constraint to improve geolocation accuracy. The results presented show the effectiveness of the MLE and DEM techniques, the sensitivity of AOA, TDOA, and T/FDOA algorithms, and the system level performance of a CubeSat geolocation cluster in a 500km circular orbit

Viability and Performance of RF Source Localization Using Autocorrelation-Based Fingerprinting

Finding the source location of a radio-frequency (RF) transmission is a useful capability for many civilian, industrial, and military applications. This problem is particularly challenging when done “Blind,” or when the transmitter was not designed with finding its location in mind, and relatively little information is available about the signal before-hand. Typical methods for this operation utilize the time, phase, power, and frequency viewable from received signals. These features are all less predictable in indoor and urban environments, where signals undergo transformation from multiple interactions with the environment. These interactions imprint structure onto the received signal which is dependent on the transmission path, and therefore the initial location. Using a received signal, a signal characteristic known as the autocorrelation can be computed which will largely be shaped by this information. In this research, RF source localization using finger-printing (a technique involving matching to a known database) with signal autocorrelations is explored. A Gaussian-process-based method for autocorrelation based fingerprinting is proposed. Performance of this method is evaluated using a ray-tracing-based simulation of an indoor environment

Investigations of 5G localization with positioning reference signals

TDOA is an user-assisted or network-assisted technique, in which the user equipment calculates the time of arrival of precise positioning reference signals conveyed by mobile base stations and provides information about the measured time of arrival estimates in the direction of the position server. Using multilateration grounded on the TDOA measurements of the PRS received from at least three base stations and known location of these base stations, the location server determines the position of the user equipment. Different types of factors are responsible for the positioning accuracy in TDOA method, such as the sample rate, the bandwidth, network deployment, the properties of PRS, signal propagation condition, etc. About 50 meters positioning is good for the 4G/LTE users, whereas 5G requires an accuracy less than a meter for outdoor and indoor users. Noteworthy improvements in positioning accuracy can be achievable with the help of redesigning the PRS in 5G technology. The accuracy for the localization has been studied for different sampling rates along with different algorithms. High accuracy TDOA with 5G positioning reference signal (PRS) for sample rate and bandwidth hasn’t been taken into consideration yet. The key goal of the thesis is to compare and assess the impact of different sampling rates and different bandwidths of PRS on the 5G positioning accuracy. By performing analysis with variable bandwidths of PRS in resource blocks and comparing all the analyses with different bandwidths of PRS in resource blocks, it is undeniable that there is a meaningful decrease in the RMSE and significant growth in the SNR. The higher bandwidth of PRS in resource blocks brings higher SNR while the RMSE of positioning errors also decreases with higher bandwidth. Also, the number of PRS in resource blocks provides lower SNR with higher RMSE values. The analysis with different bandwidths of PRS in resource blocks reveals keeping the RMSE value lower than a meter each time with different statistics is a positivity of the research. The positioning accuracy also analyzed with different sample sizes. With an increased sample size, a decrease in the root mean square error and a crucial increase in the SNR was observed. From this thesis investigation, it is inevitable to accomplish that two different analyses (sample size and bandwidth) done in a different way with the targeted output. A bandwidth of 38.4 MHz and sample size N = 700 required to achieve below 1m accuracy with SNR of 47.04 dB

Synthetic aperture source localization

2018 Summer.Includes bibliographical references.The detection and localization of sources of electromagnetic (EM) radiation has many applications in both civilian and defense communities. The goal of source localization is to identify the geographic position of an emitter of some radiation from measurements of the elds that the source produces. Although the problem has been studied intensively for many decades much work remains to be done. Many state-of-the-art methods require large numbers of sensors and perform poorly or require additional sensors when target emitters transmit highly correlated waveforms. Some methods also require a preprocessing step which attempts to identify regions of the data which come from emitters in the scene before processing the localization algorithm. Additionally, it has been proven that pure Angle of Arrival (AOA) techniques based on current methods are always suboptimal when multiple emitters are present. We present a new source localization technique which employs a cross correlation measure of the Time Dierence of Arrival (TDOA) for signals recorded at two separate platforms, at least one of which is in motion. This data is then backprojected through a Synthetic Aperture Radar (SAR)-like process to form an image of the locations of the emitters in a target scene. This method has the advantage of not requiring any a priori knowledge of the number of emitters in the scene. Nor does it rest on an ability to identify regions of the data which come from individual emitters, though if this capability is present it may improve image quality. Additionally we demonstrate that this method is capable of localizing emitters which transmit highly correlated waveforms, though complications arise when several such emitters are present in the scene. We discuss these complications and strategies to mitigate them. Finally we conclude with an overview of our method's performance for various levels of additive noise and lay out a path for advancing study of this new method through future work

Electronic Warfare Receiver Resource Management and Optimization

Optimization of electronic warfare (EW) receiver scan strategies is critical to improving the probability of surviving military missions in hostile environments. The problem is that the limited understanding of how dynamic variations in radar and EW receiver characteristics has influenced the response time to detect enemy threats. The dependent variable was the EW receiver response time and the 4 independent variables were EW receiver revisit interval, EW receiver dwell time, radar scan time, and radar illumination time. Previous researchers have not explained how dynamic variations of independent variables affected response time. The purpose of this experimental study was to develop a model to understand how dynamic variations of the independent variables influenced response time. Queuing theory provided the theoretical foundation for the study using Little\u27s formula to determine the ideal EW receiver revisit interval as it states the mathematical relationship among the variables. Findings from a simulation that produced 17,000 data points indicated that Little\u27s formula was valid for use in EW receivers. Findings also demonstrated that variation of the independent variables had a small but statistically significant effect on the average response time. The most significant finding was the sensitivity in the variance of response time given minor differences of the test conditions, which can lead to unexpectedly long response times. Military users and designers of EW systems benefit most from this study by optimizing system response time, thus improving survivability. Additionally, this research demonstrated a method that may improve EW product development times and reduce the cost to taxpayers through more efficient test and evaluation techniques