Joint Radio Frequency Fingerprints Identification via Multi-antenna Receiver

In Internet of Things (IoT), radio frequency fingerprints (RFF) technology has been widely used for passive security authentication to identify the special emitter. However, few works took advantage of independent oscillator distortions at the receiver side, and no work has yet considered filtering receiver distortions. In this paper, we investigate the RFF identification (RFFI) involving unknown receiver distortions, where the phase noise caused by each antenna oscillator is independent. Three RFF schemes are proposed according to the number of receiving antennas. When the number is small, the Mutual Information Weighting Scheme (MIWS) is developed by calculating the weighted voting of RFFI result at each antenna; when the number is moderate, the Distortions Filtering Scheme (DFS) is developed by filtering out the channel noise and receiver distortions; when the number is large enough, the Group-Distortions Filtering and Weighting Scheme (GDFWS) is developed, which integrates the advantages of MIWS and DFS. Furthermore, the ability of DFS to filter out the channel noise and receiver distortions is theoretically analyzed at a specific confidence level. Experiments are provided when both channel noise and receiver distortions exist, which verify the effectiveness and robustness of the proposed schemes

Spectral Domain RF Fingerprinting for 802.11 Wireless Devices

The increase in availability and reduction in cost of commercial communication devices (e.g. IEEE compliant such as 802.11, WiFi, 802.16, Bluetooth etc.) has increased wireless user exposure and the need for techniques to properly identify/classify signals for increased security measures. Communication device emissions include intentional modulation that enables correct device operation. Hardware and environmental factors alter the ideal response and induce unintentional modulation effects. If these effects (features) are sufficiently unique, it becomes possible to identify a device using its fingerprint, with potential discrimination of not only the manufacturer but possibly the serial number for a given manufacturer. Many techniques in many domains have been investigated to extract features, identify a fingerprint, classify signals, and each technique has certain benefits and limitations. Previous AFIT research has demonstrated the effectiveness of RF Fingerprinting using 802.11A signals with 1) spectral correlation on Power Spectral Density (PSD) fingerprints, 2) Multiple Discriminant Analysis/Maximum Likelihood (MDA/ML) classification with fingerprints obtained from Time Domain (TD) and Wavelet Domain (WD) statistical features. Performance \gain , defined as the difference in Signal-to-Noise ratio (SNR) required to achieve comparable classification performance, has been used to demonstrate considerable improvement. Spectral Domain (SD) fingerprinting uses PSD features for device discrimination. Results presented here show some improvement over the WD approach (gain ≈ 3 dB) and significant improvement over the TD approach (gain ≈ 8 dB)

Development and Demonstration of a TDOA-Based GNSS Interference Signal Localization System

Background theory, a reference design, and demonstration results are given for a Global Navigation Satellite System (GNSS) interference localization system comprising a distributed radio-frequency sensor network that simultaneously locates multiple interference sources by measuring their signals’ time difference of arrival (TDOA) between pairs of nodes in the network. The end-to-end solution offered here draws from previous work in single-emitter group delay estimation, very long baseline interferometry, subspace-based estimation, radar, and passive geolocation. Synchronization and automatic localization of sensor nodes is achieved through a tightly-coupled receiver architecture that enables phase-coherent and synchronous sampling of the interference signals and so-called reference signals which carry timing and positioning information. Signal and crosscorrelation models are developed and implemented in a simulator. Multiple-emitter subspace-based TDOA estimation techniques are developed as well as emitter identification and localization algorithms. Simulator performance is compared to the CramérRao lower bound for single-emitter TDOA precision. Results are given for a test exercise in which the system accurately locates emitters broadcasting in the amateur radio band in Austin, TX.Aerospace Engineering and Engineering Mechanic

Application of Dual-Tree Complex Wavelet Transforms to Burst Detection and RF Fingerprint Classification

This work addresses various Open Systems Interconnection (OSI) Physical (PHY) layer mechanisms to extract and exploit RF waveform features (”fingerprints”) that are inherently unique to specific devices and that may be used to provide hardware specific identification (manufacturer, model, and/or serial number). This is addressed by applying a Dual-Tree Complex Wavelet Transform (DT-CWT) to improve burst detection and RF fingerprint classification. A ”Denoised VT” technique is introduced to improve performance at lower SNRs, with denoising implemented using a DT-CWT decomposition prior to Traditional VT processing. A newly developed Wavelet Domain (WD) fingerprinting technique is presented using statistical WD fingerprints with Multiple Discriminant Analysis/Maximum Likelihood (MDA/ML) classification. The statistical fingerprint features are extracted from coefficients of a DT-CWT decomposition. Relative to previous Time Domain (TD) results, the enhanced WD statistical features provide improved device classification performance. Additional performance sensitivity results are presented to demonstrate WD fingerprinting robustness for variation in burst location error, MDA/ML training and classification SNRs, and MDA/ML training and classification signal types. For all cases considered, the WD technique proved to be more robust and exhibited less sensitivity when compared with the TD Technique

Development of high speed power thyristor: The gate assisted turn-off thyristor

A high speed power switch with unique turn-off capability was developed. This gate-assisted turn-off thyristor was rated at 609 V and 50 A with turn-off times of 2 microsec. Twenty-two units were delivered for evaluation in a series inverter circuit. In addition, test circuits designed to relate to the series inverter application were built and demonstrated

Exciton Footprint of Self-assembled AlGaAs Quantum Dots in Core-Shell Nanowires

Quantum-dot-in-nanowire systems constitute building blocks for advanced photonics and sensing applications. The electronic symmetry of the emitters impacts their function capabilities. Here, we study the fine structure of gallium-rich quantum dots nested in the shell of GaAs-AlGaAs core-shell nanowires. We used optical spectroscopy to resolve the splitting resulting from the exchange terms and extract the main parameters of the emitters. Our results indicate that the quantum dots can host neutral as well as charges excitonic complexes and that the excitons exhibit a slightly elongated footprint, with the main axis tilted with respect to the growth axis. GaAs-AlGaAs emitters in a nanowire are particularly promising for overcoming the limitations set by strain in other systems, with the benefit of being integrated in a versatile photonic structure

A determination of the risk of intentional and unintentional electromagnetic radiation emitters degrading installed components in closed electromagnetic environments

This report proposes a method of risk determination that incorporates a loss function and a probability function in order to better enable decision makers in determining the risk of implementing wireless technologies in reverberant enclosed spaces that contain sensitive installed components. There is a constant desire to include new technology into the systems being designed to operate onboard U.S. Naval vessels. One of these technologies is wireless communications. This technology relies on the use of the electromagnetic spectrum in order to transfer information from one point to another. This type of information transfer can be advantageous in various applications. Exposing sensitive electronic components to a time-varying electromagnetic field increases the risk of an electronic upset in those components that will degrade the functionality of installed systems. This risk determination should provide a way to weigh the risk of introducing wireless technologies in enclosed spaces. This risk determination relies on the assumption that at some point there will be enough data collected to properly determine the overall risk to at-risk equipment. Until that occurs, incorporating new methods of shielding and low power technologies is recommended.http://archive.org/details/adeterminationof1094545882Lieutenant Commander, United States NavyApproved for public release; distribution is unlimited

MULTISTATIC RADAR EMITTER IDENTIFICATION USING ENTROPY MAXIMIZATION BASED INDEPENDENT COMPONENT ANALYSIS

Radar emitter identification is state-of-the-art in modern electronic warfare. Presently multistatic architecture is adapted by almost all the radar systems for better tracking performance and accuracy in target detection. Hence, identification and classification of radar emitters operating in the surveillance region are the major problems. To deal with the difficulty of identification of radar emitters in a complex electromagnetic environment, in this work entropy maximization method of Independent Component Analysis (ICA) based on gradient ascent algorithm is proposed. This algorithm separates unknown source signals from the interleaved multi-component radar signals. The discrete source signals are extracted from the multi-component signal by optimizing the entropy where maximum entropy is achieved using a gradient ascent approach through unsupervised learning. As better detection capability and range resolution are achieved by Linear Frequency Modulated (LFM) signals for radar systems here, multicomponent LFM signals with low SNR are considered as the signal mixture from which, the independent sources separated. A mathematical model of the algorithm for entropy maximization is illustrated in this paper. Simulation result validates the effectiveness of the algorithm in terms of time domain separation of the signal, and time-frequency analysi

Space shuttle electromagnetic environment experiment. Phase A: Definition study

Methods for carrying out measurements of earth electromagnetic environment using the space shuttle as a measurement system platform are herein reported. The goal is to provide means for mapping intentional and nonintentional emitters on earth in the frequency range 0.4 to 40 GHz. A survey was made of known emitters using available data from national and international regulatory agencies, and from industry sources. The spatial distribution of sources, power levels, frequencies, degree of frequency re-use, etc., found in the survey, are here presented. A concept is developed for scanning the earth using a directive antenna whose beam is made to rotate at a fixed angle relative to the nadir; the illuminated area swept by the beam is of the form of cycloidal annulus over a sphere. During the beam's sojourn over a point, the receiver sweeps in frequency over ranges in the order of octave width using sweeping filter bandwidths sufficient to give stable readings