742 research outputs found
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 â 3 dB) and significant improvement over the TD approach (gain â 8 dB)
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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 signalsâ
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 (âfingerprintsâ) 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 âDenoised VTâ 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
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