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At least 253 records · Page 14

Creation of Speed-of-Sound Inject Data for Technical Nuclear Forensics

Technical Nuclear Forensics (TNF) exercises simulate a detonation of a nuclear device within the United States, usually in a city. Speed-of-sound (SOS) phenomenology are the atmospheric overpressure and ground shock mechanical motions that are observed at over-pressure (air-blast and infrasound) and seismic sensors, respectively (Figure 1). Amplitudes of SOS data are related to the explosive yield (Kinney and Graham, 1985; Koper et al., 2002; Bonner et al., 2013ab; Ford et al., 2014, 2021; Templeton et al., 2018; Schnurr et al., 2020). Within the country, the United States Prompt Diagnostics System (USPDS) includes a network of geophysical sensors to capture such SOS signals. During the TNF exercise, the event data will be analyzed by the players who know nothing about the technical details of the source (e.g. location, yield, explosive). Specifically, they will use the Integrated Yield Determination Tool (IYDT) to estimate the yield and height-of-burst or depth-of-burial (HOB/DOB). The IYDT allows the user to measure features on the overpressure and seismic channels, evaluate the consistency of features and jointly estimate yield and HOB/DOB. For these exercises, SOS data are simulated for the location, emplacement and yield of the device and signals are propagated to the observing stations. This document describes the steps undertaken in the simulation, validation, preparation and verification of SOS signals for TNF exercises.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Results of CoSMIR Under-Flights of the SSMIS

The first copy of the SSMIS (Special Sensor Microwave/Imager/Sounder) was launched on board the DMSP (Defense Meteorological Satellite Project) F-16 satellite in October 2003. During March-April 2004, six 5-hour SSMIS under-flights were conducted with the CoSMIR on board the NASA ER-2 aircraft over the coastal region of California. CoSMIR has nine channels at the frequencies of 50.3, 52.8, 53.6, 91.665 (V and H polarization), 150, 183.3+/-1, 183.3+/-3, and 183.3+/-6.6 GHz. All except the two 91.665 GHz channels are horizontally polarized. The instrument was carefully calibrated with LN2 target in the laboratory before the flights. Three of the aircraft flights passed over Lakes Pyramid and Tahoe that could be used to validate the in-flight sensor calibration. Immediately after these flights, an inter-comparison of the calibrated SSMIS and CoSMIR brightness temperatures (T(sub b)) followed. The results showed that, for channels at frequencies > or equal to 91.665 GHz, the SSMIS and CoSMIR T(sub b) values tracked each other very well; for some channels there were some bias with magnitude generally less than 3-4 K (SSMIS values were higher). For the three 50-54 GHz channels, the SSMIS T(sub b) values were higher and frequency-dependent. For the least opaque channel at 50.3 GHz, the SSMIS T(sub b)'s over the ocean surface were higher than those of CoSMIR by more than 20 K under the clear-sky conditions. The most plausible explanation for this to happen is to assume that the 50-54 GHx channels of the SSMIS are vertically polarized. This assumption appears to be consistent with independent radiative transfer calculations. Attempts to estimate vertically polarized radiometric responses for 50-54 GHz channels of the SSMIS based on the CoSMIR observations are not plausible and results not reliable because of the highly variable ocean surface conditions (e.g., wind-induced emissivity changes). A conversion of the CoSMIR 50-54 GHz channels from horizontal to vertical polarization, and a subsequent repetition of the SSMIS under-flights are the right approach for the calibration/validation of the 50-54 GHz channels of the SSMIS. Details of the SSMIS-CoSMIR inter-comparison will be presented.

Wang, J. R.↗

Multiple-beam satellite repeater tradeoffs applied to a multifunctional system.

This paper concerns satellite repeater tradeoffs for a multiple-beam, multiple-channel, multiple-connectivity satellite postulated to serve a diversity of domestic U.S. noncommercial requirements, with a substantial portion of the satellite power, weight, and bandwidth dedicated to video distribution and bradcast. The orders-of-magnitude of the requirements are given for the video plus high-rate data traffic category. The designs of two alternative baseline repeater configurations are presented, and estimates of their weight and their prime power consumption are given. These data are the basis for estimating the weight and power consumption of a range of alternative beam coverage, modulation, and channel capacity systems. These estimates are used to illustrate tradeoffs with different performance criteria as the independent variable: number of channels per beam and total number of beam-channels.

Kinal, G. V.↗

Separation of cirrus cloud from clear surface from AVIRIS data using the 1.38 micron water vapor band

Cirrus clouds play an important role in climate systems because of their large area coverage, persistence, and radiative effects. Thin cirrus clouds are difficult to detect in visible images and infrared images in the 10-12 micron atmospheric window region, particularly over land, because these clouds are partially transparent. Ackerman recently developed a method for detecting cirrus clouds using three narrow channels centered near 8, 11, and 12 microns, respectively, based on the analysis of IR emission spectra measured with a high spectral resolution interferometer. Barton also described a method for estimating cirrus cloud height and amount from measurements with two narrow channel radiometers of the Selective Chopper Radiometer on Nimbus 5. Both channels are located within the strong 2.7 micron water vapor band absorption region. One of the channels includes additional carbon dioxide absorption. A differential absorption technique with sets of empirical coefficients was used in the estimation of cirrus cloud heights and amounts. A technique using narrow channels in the strong 1.38 micron water vapor band absorption region for detecting cirrus clouds from spectral imaging data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) on 5 Dec. 1991 during the FIRE (The First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment) Phase 2 Field Experiment is described.

Gao, Bo-Cai↗

A bi-channel aided stitching of atomic force microscopy images

Microscopy is an essential tool in scientific research, enabling the visualization of structures at micro- and nanoscale resolutions. However, the field of microscopy often encounters limitations in field-of-view (FOV), restricting the amount of sample that can be imaged in a single capture. To overcome this limitation, image stitching techniques have been developed to seamlessly merge multiple overlapping images into a single, high-resolution composite. The images collected from microscope need to be optimally stitched before accurate physical information can be extracted from post analysis. However, the existing stitching tools either struggle to stitch images together when the microscopy images are feature sparse or cannot address all the transformations of images when performing image stitching. To address these issues, we propose a bi-channel aided feature-based image stitching method and demonstrate its use on Atomic Force Microscopy (AFM) generated Pantoea sp. YR343 biofilm and PTO thin film sample images as experimental data. The topographical channel image of AFM data captures the morphological details of the sample, and a stitched topographical image is desired for researchers. We utilize the amplitude and phase channels of AFM data to maximize the matching features and to estimate the position of the original topographical images and show that the proposed bi-channel aided stitching method outperforms the traditional direct stitching approach in AFM topographical image stitching task. Here, we demonstrated the application on AFM, but similar approaches could be employed of optical microscopy with brightfield and fluorescence channels. We believe this proposed workflow can serve as a valuable augmentation strategy for microscopy image stitching tasks and will benefit the experimentalist to avoid erroneous analysis and discovery due to incorrect stitching.

Atomic force microscopy↗

Enhanced heavy oil recovery by low salinity polymer flood combined with microgel treatment

“Heavy oil resources account for a large portion of the total oil reserves around the world. The target heavy oil reservoir is located on Alaska’s North Slope (ANS). Advantages of low-salinity HPAM polymer (LSP) over high-salinity polymer (HSP) were demonstrated. LSP could recover more oil with 40% less polymer consumption. No additional oil was recovered by HSP after LSP flood. The first-ever polymer flood pilot on ANS showed remarkable success regarding water cut reduction, oil production increase, delayed breakthrough, and projected oil recovery improvement. Polymer alone was insufficient to achieve satisfactory recovery as the reservoirs were highly heterogeneous. Microgels could improve the effectiveness of polymer flood by reducing water cut and increasing oil recovery. Favorable working conditions were identified. Microgel transport behavior was studied using superpermeable sandpacks (27-221 darcies) with multiple pressure sensors. The particle-to-pore matching size ratio significantly impacted the effectiveness of the gels. A threshold differential pressure (ΔPth) and critical pressure gradient (∇Pcr) were required to push the gels to penetrate and propagate through the channels. The ΔPth and ∇Pcr revealed the underlying mechanisms of selective penetration/placement behavior of microgels in heterogeneous reservoirs. Diagrams were developed to estimate the maximum propagation distance of the gels in channels in conceptual field applications. Sandwich-like channel models and methodologies were developed to comprehensively evaluate the effectiveness of gel materials. Gel retention in the channels was quantified. Results also indicated that the retained gels were dehydrated. Fluid diversion and sweep improvement after gel treatments were evaluated by tracer tests”--Abstract, page iv.

Zhao, Yang↗

FY19 FES Theory Performance Target (Final Report)

Understanding the relevant turbulent transport mechanisms at the edge of a high-performance tokamak is essential for predicting and optimizing the H-mode pedestal structure in future burning plasma devices. Global electromagnetic gyrokinetic simulations will be performed based on representative experimental pedestal scenarios in order to clarify which instabilities are most important for each of the particle and heat transport channels. Edge transport modeling will be performed in order to estimate and bound the particle and heat sources—e.g., the ionization density source and the atomic energy loss channels due to ionization, charge exchange, and radiation. Comparisons will be made with data from the DIII-D, JET, C-Mod and NSTX or MAST experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Infrared Emission Spectroscopy as a Reliability Tool

In this paper we report on a technique based on infrared emission spectroscopy which has been found to be useful for non-contact measurement of the temperature of a hot spot in the gate channel of a GaAs metal/semiconductor field effect transistor (MESFET). The technique was demonstrated on a powered and un-powered GaAs MESFET attaining a spatial resolution of 0.5 microns. A non-destructive submicron-size spot laser beam provided by an HeNe laser excites an extremely small local area of the gate channel of a GaAs MESFET under various operating conditions. Given the state of the experimental test system, we estimate a spatial resolution of about 0.1 microns and a spectral resolution of about 0. I Angstroms. This provides 15 - 100 times finer spatial resolution than can be obtained using the best passive IR systems available. The temperature resolution (less than 0.02 K/micron) of this technique is depend upon the spectrometer used, and that it can be improved further. The information obtained from this technique can be used to estimate device lifetimes for critical applications and for measurement of channel temperature of devices under actual operating conditions. Another potential use of the novel technique can be as a cost-effective prescreening tool for determining the "hot spot" channel temperature of devices under normal operating conditions which can further improve device design, yield enhancement, and reliable operation

Kim, Q.↗

Satellite sensor estimates of Northern Hemisphere snow volume

In the Northern Hemisphere the mean monthly snow-covered area ranges from about 7 percent of the land area in summer to over 40 percent in winter, thus making snow one of the most rapidly varying natural surface features. The mean monthly snow volume ranges from about 1.5 x 10 to the 16th g in summer to about 3.0 x 10 to the 18th g in winter. Currently several algorithms utilizing passive microwave brightness temperatures are available to estimate snow cover and depth. The algorithm presented here uses the difference between the 37-GHz channel and the 18-GHz channel of the SMMR on the Nimbus-7 satellite to derive estimates of snow volume. Even though satellite sensor snow records are currently too short to reveal trends, continued monitoring over about the next 10 years should make it possible to establish whether incipient or current trends are significant in the context of global climate change.

Chang, A. T. C.↗

Aircraft Engine On-Line Diagnostics Through Dual-Channel Sensor Measurements: Development of an Enhanced System

In this paper, an enhanced on-line diagnostic system which utilizes dual-channel sensor measurements is developed for the aircraft engine application. The enhanced system is composed of a nonlinear on-board engine model (NOBEM), the hybrid Kalman filter (HKF) algorithm, and fault detection and isolation (FDI) logic. The NOBEM provides the analytical third channel against which the dual-channel measurements are compared. The NOBEM is further utilized as part of the HKF algorithm which estimates measured engine parameters. Engine parameters obtained from the dual-channel measurements, the NOBEM, and the HKF are compared against each other. When the discrepancy among the signals exceeds a tolerance level, the FDI logic determines the cause of discrepancy. Through this approach, the enhanced system achieves the following objectives: 1) anomaly detection, 2) component fault detection, and 3) sensor fault detection and isolation. The performance of the enhanced system is evaluated in a simulation environment using faults in sensors and components, and it is compared to an existing baseline system.

Kobayashi, Takahisa↗

A minicomputer based software system for the selection of optimal subsets of Thematic Mapper channels

A software system has been developed and implemented on a minicomputer for feature selection based on two inter-dependent methods. The first is an enhancement of the traditional approach based on optimizing interclass average separabilities. The second is based on a Monte Carlo simulation of multispectral data and machine classification with subsequent estimation of classification accuracy as a function of channel subset. The two methods are mutually supportive - the first allows rapid screening whereas the second is based on the more solid theoretical foundation of maximizing classification accuracy.

Card, D. H.↗

Data Assimilation Experiments Using Quality Controlled AIRS Version 5 Temperature Soundings

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains a number of significant improvements over Version 4. Two very significant improvements are described briefly below. 1) The AIRS Science Team Radiative Transfer Algorithm (RTA) has now been upgraded to accurately account for effects of non-local thermodynamic equilibrium on the AIRS observations. This allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval algorithm during both day and night. Following theoretical considerations, tropospheric temperature profile information is obtained almost exclusively from clear column radiances in the 4.3 micron CO2 band in the AIRS Version 5 temperature profile retrieval step. These clear column radiances are a derived product that are indicative of radiances AIRS channels would have seen if the field of view were completely clear. Clear column radiances for all channels are determined using tropospheric sounding 15 micron CO2 observations. This approach allows for the generation of accurate values of clear column radiances and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel clear column radiances. These error estimates are used for quality control of the retrieved products. Based on error estimate thresholds, each temperature profiles is assigned a characteristic pressure, pg, down to which the profile is characterized as good for use for data assimilation purposes. We have conducted forecast impact experiments assimilating AIRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the NASA FVGCM, at a spatial resolution of 0.5 deg by 0.5 deg. Assimilation of Quality Controlled AIRS temperature profiles down to pg resulted in significantly improved forecast skill compared to that obtained from experiments when all data used operationally by NCEP, except for AIRS data, is assimilated. These forecasts were also significantly better than to those obtained when AIRS radiances (rather than temperature profiles) are assimilated, which is the way AIRS data is used operationally by NCEP and ECMWF.

Susskind, Joel↗

Hyporheic‐Zone Processes and Stream Oxygen Dynamics: Insights From a Multiscale Reactive Transport Model

Aquatic ecosystem metabolism encapsulates the daily fixation (gross primary production, GPP d ) and mineralization (ecosystem respiration, ER d ) of organic carbon. In fluvial systems, these are commonly estimated by inverse solutions to field observations using a model that describes oxygen concentrations varying in the water column in response to metabolic fluxes and air‐water gas exchange controlled by a rate coefficient (K 600 ). The most common conceptual model is the single‐station metabolism (SSM) model. The simplicity and flexibility of this conceptualization make it attractive; however, it implicitly assumes that all the processes that consume oxygen in fluvial systems can be lumped into a bulk estimate of respiration with poorly understood consequences for estimates of GPP d , ER d , and K 600 . Here, we focus on the implications of using SSM conceptualization when estimating metabolic fluxes from oxygen dynamics in channels where hyporheic exchange occurs. We use a new multiscale numerical model for reactive transport in streams that represents hyporheic exchange and streambed heterotrophic respiration. Nondimensionalization of this model reveals dimensionless groups that collectively control oxygen dynamics. Numerical experiments offer a mechanistic understanding of the impacts of hyporheic exchange on diel oxygen dynamics revealing that potential biases arise from neglecting mass transfer limitations. Specifically, we found that hyporheic exchange significantly affects diel oxygen dynamics, even for nonreactive streambed sediments. Moreover, while the SSM performs well in many situations, we find conditions where significant bias is produced by hyporheic exchange, even when oxygen data are well‐fitted. These situations pose a major challenge in the interpretation of metabolism assessment estimates.

Gomez‐Velez, Jesus D. [Oak Ridge National Laborato↗

Systematic Differences between Satellite-Based Presipitation Climatologies over the Tropical Oceans

Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. It is clear however that there still remain significant uncertainties with satellite precipitation retrievals which limit their usefulness for many purposes. Systematic differences i'A tropical precipitation estimates have been brought to light in comparison activities such as the GPCP Algorithm Intercomparison Project and more recent Wetnet Precipitation Intercomparison Project 3. These uncertainties are assuming more importance because of the demands for validation associated with global climate modeling and data assimilation methodologies. The objective of the present study is to determine the physical basis for systematic differences in spatial structure of tropical precipitation as portrayed by several different satellite-based data sets. The study is limited to oceanic regions only and deals primarily with aspects of spatial variability. We are specifically interested in why MSU channel 1 and GPI precipitation differences are so striking over the Eastern Pacific ITCZ and why they both differ from other microwave emission-based precipitation estimates from SSM/I and a scattering-based deep convective ice index from MSU channel 2. Our results to date have shown that MSU channel I precipitation estimates are biased high over the Eastern Pacific ITCZ because of two factors: (1) the hypersensitivity of this frequency to cloud water in contrast to falling rain drops, and (2) unaccounted for scattering effects by precipitation-size ice which depresses the signal of the liquid water emission. Likewise, cold cloud top climatologies such as the GPI show an excess (a deficit) in estimated rainfall over the E. Pacific ITCZ (Warm Pool region). We show that these algorithms need to account for regionally varying heights (or temperatures) at which tropical convection detrains to form cirrus shields. A second objective we pursue is to identify variations in the macroscale cloud physical and thermodynamic properties of precipitation regimes" and relate these differences to tropical dynamical mechanisms of tropical heat and moisture balance. Finally, we interpret the algorithm differences and their associations with tropical dynamics in terms of WCRP GPCP goals for constructing precipitation climatologies.

Robertson, Frankin R.↗

Combining Ratio Estimation for Low Density Parity Check (LDPC) Coding

The Low Density Parity Check (LDPC) Code decoding algorithm make use of a scaled receive signal derived from maximizing the log-likelihood ratio of the received signal. The scaling factor (often called the combining ratio) in an AWGN channel is a ratio between signal amplitude and noise variance. Accurately estimating this ratio has shown as much as 0.6 dB decoding performance gain. This presentation briefly describes three methods for estimating the combining ratio: a Pilot-Guided estimation method, a Blind estimation method, and a Simulation-Based Look-Up table. The Pilot Guided Estimation method has shown that the maximum likelihood estimates of signal amplitude is the mean inner product of the received sequence and the known sequence, the attached synchronization marker (ASM) , and signal variance is the difference of the mean of the squared received sequence and the square of the signal amplitude. This method has the advantage of simplicity at the expense of latency since several frames worth of ASMs. The Blind estimation method s maximum likelihood estimator is the average of the product of the received signal with the hyperbolic tangent of the product combining ratio and the received signal. The root of this equation can be determined by an iterative binary search between 0 and 1 after normalizing the received sequence. This method has the benefit of requiring one frame of data to estimate the combining ratio which is good for faster changing channels compared to the previous method, however it is computationally expensive. The final method uses a look-up table based on prior simulated results to determine signal amplitude and noise variance. In this method the received mean signal strength is controlled to a constant soft decision value. The magnitude of the deviation is averaged over a predetermined number of samples. This value is referenced in a look up table to determine the combining ratio that prior simulation associated with the average magnitude of the deviation. This method is more complicated than the Pilot-Guided Method due to the gain control circuitry, but does not have the real-time computation complexity of the Blind Estimation method. Each of these methods can be used to provide an accurate estimation of the combining ratio, and the final selection of the estimation method depends on other design constraints.

Mahmoud, Saad↗

Daily Rainfall Estimate by Emissivity Temporal Variation from 10 Satellites

Rainfall retrieval algorithms for passive microwave radiometers often exploit the brightness temperature depression due to ice scattering at high-frequency channels (≥85 GHz) over land. This study presents an alternate method to estimate the daily rainfall amount using the emissivity temporal variation (i.e., Δe) under rain-free conditions at low-frequency channels (19, 24, and 37 GHz). Emissivity is derived from 10 passive microwave radiometers, including the Global Precipitation Measurement (GPM) Microwave Imager (GMI), the Advanced Microwave Scanning Radiometer 2 (AMSR2), three Special Sensor Microwave Imager/Sounders (SSMIS), the Advanced Technology Microwave Sounder (ATMS), and four Advanced Microwave Sounding Units-A (AMSU-A). Four different satellite combination schemes are used to derive the Δe for daily rainfall estimates. They are all 10 satellites, 5 imagers, 6 satellites with very different equator crossing times, and GMI only. Results show that Δe from all 10 satellites has the best performance with a correlation of 0.60 and RMSE of 6.52 mm, compared with the Integrated Multisatellite Retrievals for GPM (IMERG) Final run product. The 6-satellites scheme has comparable performance with the all-10-satellites scheme. The 5-imagers scheme performs noticeably worse with a correlation of 0.49 and RMSE of 7.28 mm, while the GMI-only scheme performs the worst with a correlation of 0.25 and RMSE of 11.36 mm. The inferior performance from the 5-imagers and GMI-only schemes can be explained by the much longer revisit time, which cannot accurately capture the emissivity temporal variation.

Yalei You↗

An Instrument to Enable Identification of Anthropogenic CO2 Emissions Using Concurrent CO Measurements

We have developed an instrument concept that will enable the measurement of CO from the top of the atmosphere to the Earth's surface with very high sensitivity and at the high spatial and temporal resolutions required by the NRC Decadal Survey mission Active Sensing of Carbon Dioxide (CO2) over Nights, Days and Seasons (ASCENDS). We are developing an innovative CO sensor that will enable the ASCENDS mission to differentiate between anthropogenic and natural sources and sinks of global carbon. The NRC Decadal Survey places particular emphasis on retrieving CO information for the planetary boundary layer. Measurement made using both the 2.3 micron and 4.7 micron channels are needed to achieve the sensitivity required in the lower atmosphere where the degree of CO - CO2 correlation is indicative of anthropogenic sources of CO2. Measurements made using only the 4.7 micron channel cannot provide sufficient sensitivity to CO in the very lowest layers of the atmosphere. The fundamental method we use is Gas Filter Correlation Radiometry (GFCR), a highly successful technique used in other airborne and space-based missions for detecting trace species in the Earth's atmosphere. Our version of GFCR overcomes many of the limitations encountered by prior and existing instruments, allowing us to measure weak signals from small targets very quickly and with extremely high specificity by employing a new dual beam radiometer concept using a focal plane array. Our design will provide a means to make the desired CO measurements for the ASCENDS mission. A simple change in gas filter cell contents would allow the same hardware to measure CH4 with high precision under the nominal ASCENDS mission spatial and temporal constraints. All critical components in the sensor design are mature, many subsystems tested, and the system has been extensively modeled, bringing it to a present Technology Readiness Level (TRL) of 3 (though some individual components are at TRLs 6-9). We are presently developing critical components for the new spectrometer and advancing our understanding of the measurement requirements for both CO and CH4. This new GFCR technique/sensor will enable measurements of trace gases with high sensitivity while maintaining the inherent robustness and simplicity of the more traditional radiometer hardware. Initial estimates of cost/risk of a spacebased 2-channel GFCR indicate that our design is extremely cost effective and will fit within existing ASCENDS mission budget constraints as determined by the NRC Decadal Survey and a NASA-sponsored mission study.

Cook, William B.↗

Autonomous Wireless Technology Detection in Seamless IoT Applications

The ever-increasing use of Internet of Things (IoT) devices results in the implementation of multiple wireless technologies that would not only cater their data rate requirements but also support various applications. To optimize the energy efficiency and security of the wireless transmission, it is imperative to identify the wireless technologies in various IoT implementations. Many of the existing approaches are based on measuring only the receiving signal strength indicator (RSSI). However, such approaches may not work well because of transmit power control and complex channel variations among different wireless technologies. In this article, we propose an autonomous wireless detection scheme that considers multiple distinguishable physical (PHY)-layer settings for real-time identification of wireless technologies for real-time applications. Specifically, the proposed scheme relies on the PHY-layer measurements of the targeted spectrum. Transmission settings, such as bandwidth, carrier frequency, and RSSI are estimated from the raw in-phase and quadrature-phase (I/Q) measurements. In addition, a symbol-level extraction scheme is implemented to extract unique features of modulation settings. These aforementioned features are applied to a machine learning process to identify the received wireless technologies. Compared with raw I/Q measurements, the extracted features are much simplified and, thus, the machine learning classifier can be designed with a simple structure for fast processing on IoT nodes. Finally, the proposed schemes are primarily evaluated theoretically, followed by implementing them on a USRP software-defined radio (SDR)-based hardware testbed. The evaluation results demonstrate high accuracy in the real-time detection of different wireless technologies for seamless IoT applications.

42 ENGINEERING↗