scholarly journals Clutter-Masked Waveform Design for LPI/LPD Radarcom Signal Encoding

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 631
Author(s):  
Richard Washington ◽  
Brenton Bischof ◽  
Dmitriy Garmatyuk ◽  
Saba Mudaliar
Keyword(s):  
Design Method ◽  
Random Sequence ◽  
Laboratory Data ◽  
Radar Data ◽  
Communication Security ◽  
Secure Communications ◽  
Signal Encoding ◽  
Sequence Encoding ◽  
Radar Sensing

In this work we propose a method of in situ clutter deconvolution and modeling using experimentally obtained UWB radar data. The obtained clutter models are then used for random sequence encoding of radar-communication (radarcom) signals to achieve clutter-masked transmissions and improve communication security. We present the results of clutter modeling from the laboratory data obtained with the software-defined radar system. We then show that such clutter-masked radarcom signals generated using the local clutter model are highly likely to be interpreted as just clutter returns by an unauthorized interceptor. We also present the results of communication and radar performance of these radarcom signals and contrast them with those obtained using a linear frequency modulated waveform. It is shown that the proposed radarcom design method has high potential to achieve secure communications in adversarial conditions, while simultaneously addressing radar sensing needs.

Mathematical Model Investigation of Far-Field Transport of Ocean-Dumped Sewage Sludge Related to Remote Sensing

1982 ◽  
Vol 14 (3) ◽  
pp. 33-39
Author(s):  
C Y Kuo
Keyword(s):  
New York ◽  
Sewage Sludge ◽  
Laboratory Data ◽  
Three Dimensional ◽  
Approximate Model ◽  
Transport Processes ◽  
Far Field ◽  
New York Bight ◽  
Mean Current

An existing, three-dimensional, Eulerian-Lagrangian finite-difference model was modified and used to examine the far-field transport processes of dumped sewage sludge in the New York Bight. Both in situ and laboratory data were utilized in an attempt to approximate model inputs such as mean current speed, vertical and horizontal diffusion coefficients, particle size distributions, and specific gravities. Concentrations of the sludge near the sea surface predicted from the computer model were compared qualitatively with those remotely sensed.

scholarly journals Cutting Resistance Laboratory Testing Methodology for Underwater Coal Mining

Minerals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 564
Author(s):  
Vladimir Čebašek ◽  
Veljko Rupar ◽  
Stevan Đenadić ◽  
Filip Miletić
Keyword(s):  
Coal Mining ◽  
Laboratory Testing ◽  
Water Pressure ◽  
Laboratory Data ◽  
Working Environment ◽  
Laboratory Research ◽  
Surrounding Water ◽  
Cutting Resistance ◽  
Testing Methodology

The bucket-wheel dredge “Kovin I” for underwater coal mining with bucket-wheel type UCW-450 has been in operation for over 20 years. Based on analyzing the bucket-wheel dredger performance, productivity, maintenance costs, and reliability, a rational decision was made: to rehabilitate the most essential parts of the dredge, including the bucket wheel and the gearbox. However, the selection and construction of the excavator parts were performed on the ground of available laboratory data for digging resistance. The data itself was determined by the testing methodology that did not include the influence of surrounding water pressure at a certain depth of mining. According to the previous findings, it was necessary to develop a specific research and testing program that would involve appropriate laboratory testing of the geomechanical parameters. These were to represent the influence of hydrostatic water pressure on the working environment—coal. Nevertheless, geomechanical laboratory research tests were initially modified to provide reliable data of cutting resistance, especially in the water under different hydrostatic pressures, fully simulating the “in situ” working conditions of mining, i.e., cutting.

Polarimetric Radar Rain Estimation through Retrieval of Drop Size Distribution Using a Bayesian Approach

2010 ◽  
Vol 49 (5) ◽  
pp. 973-990 ◽  
Author(s):  
Qing Cao ◽  
Guifu Zhang ◽  
Edward A. Brandes ◽  
Terry J. Schuur
Keyword(s):  
Bayesian Approach ◽  
Mesoscale Convective System ◽  
Radar Data ◽  
Normal Function ◽  
In Situ Measurements ◽  
Retrieval Algorithm ◽  
Convective System ◽  
Horizontal Polarization ◽  
Oklahoma Mesonet

Abstract This study proposes a Bayesian approach to retrieve raindrop size distributions (DSDs) and to estimate rainfall rates from radar reflectivity in horizontal polarization ZH and differential reflectivity ZDR. With this approach, the authors apply a constrained-gamma model with an updated constraining relation to retrieve DSD parameters. Long-term DSD measurements made in central Oklahoma by the two-dimensional video disdrometer (2DVD) are first used to construct a prior probability density function (PDF) of DSD parameters, which are estimated using truncated gamma fits to the second, fourth, and sixth moments of the distributions. The forward models of ZH and ZDR are then developed based on a T-matrix calculation of raindrop backscattering amplitude with the assumption of drop shape. The conditional PDF of ZH and ZDR is assumed to be a bivariate normal function with appropriate standard deviations. The Bayesian algorithm has a good performance according to the evaluation with simulated ZH and ZDR. The algorithm is also tested on S-band radar data for a mesoscale convective system that passed over central Oklahoma on 13 May 2005. Retrievals of rainfall rates and 1-h rain accumulations are compared with in situ measurements from one 2DVD and six Oklahoma Mesonet rain gauges, located at distances of 28–54 km from Norman, Oklahoma. Results show that the rain estimates from the retrieval agree well with the in situ measurements, demonstrating the validity of the Bayesian retrieval algorithm.

Assessment of Moisture Content in Sandy Beach Environments from Multispectral Satellite Imagery

2021 ◽  
Author(s):  
Julie Paprocki ◽  
Nina Stark ◽  
Hans C Graber ◽  
Heidi Wadman ◽  
Jesse E McNinch
Keyword(s):  
Moisture Content ◽  
Laboratory Data ◽  
Field Measurements ◽  
Weather Conditions ◽  
Sandy Beaches ◽  
Percent Error ◽  
Moisture Contents ◽  
Multispectral Satellite Imagery ◽  
Factor C

A framework for estimating moisture content from satellite-based multispectral imagery of sandy beaches was tested under various site conditions and sensors. It utilizes the reflectance of dry soil and an empirical factor c relating reflectance and moisture content for specific sediment. Here, c was derived two ways: first, from in-situ measurements of moisture content and average NIR image reflectance; and second, from laboratory-based measurements of moisture content and spectrometer reflectance. The proposed method was tested at four sandy beaches: Duck, North Carolina, and Cannon Beach, Ocean Cape, and Point Carrew, Yakutat, Alaska. Both measured and estimated moisture content profiles were impacted by site geomorphology. For profiles with uniform slopes, moisture contents ranged from 3.0%-8.0% (Zone 1) and from 8.0%-23.0% (Zone 2). Compared to field measurements, the moisture contents estimated using c calibrated from in-situ and laboratory data resulted in percent error of 3.6%-44.7% and 2.7%-58.6%, respectively. The highest percent error occurred at the transition from Zone 1 to Zone 2. Generally, moisture contents were overestimated in Zone 1 and underestimated in Zone 2, but followed the expected trends based on field measurements. When estimated moisture contents in Zone 1 exceeded 10%, surface roughness, debris, geomorphology, and weather conditions were considered.

scholarly journals Polarimetric radar observations during an orographic rain event and the performance of a hydrometeor classification scheme

2014 ◽  
Vol 11 (7) ◽  
pp. 8845-8877
Author(s):  
M. Frech ◽  
J. Steinert
Keyword(s):  
Classification Scheme ◽  
Ground Level ◽  
Radar Data ◽  
Precipitation Event ◽  
Orographic Precipitation ◽  
Rain Event ◽  
Melting Layer ◽  
Surface Observation ◽  
Meteorological Observatory ◽  
Radar Sensing

Abstract. An intense orographic precipitation event is analysed using two polarimetric C-Band radars situated north of the Alps on 5 January 2013. One radar is operated at DWD's meteorological observatory Hohenpeißenberg (MHP, 1006 m a.s.l. – above sea level) and the Memmingen (MEM, 65 km west of MHP, 600 m a.s.l.) radar is part of DWD's operational radar network. The event lasted about 1.5 days and in total 44 mm precipitation was measured at Hohenpeißenberg. Detailed high resolution observation on the vertical structure of this event is obtained through a birdbath scan at 90° elevation which is part of the operational scanning. This scan is acquired every 5 min and provides meteorological profiles at high spatial resolution. In the course of this event, the melting layer (ML) descends until the transition from rain into snow is observed at ground level. This transition from rain into snow is well documented by local weather observers and a present-weather sensor. The orographic precipitation event reveals mesoscale variability above the melting layer which is unexpected from a meteorological point of view. It corresponds to a substantial increase in rain rate at the surface. The performance of the newly developed hydrometeor classification scheme "Hymec" using Memmingen radar data over Hohenpeißenberg is analyzed. The detection in location and timing of the ML agrees well with the Hohenpeißenberg radar data. Considering the size of the Memmingen radar sensing volume, the detected hydrometeor (HM) types are consistent for measurements at or in a ML, even though surface observation indicate for example rain whereas the predominant HM is classified as wet snow. To better link the HM classification with the surface observation, either better thermodynamic input is needed for Hymec or a statistical correction of the HM classification similar to a model output statistics (MOS) approach may be needed.

scholarly journals Augmenting biologging with supervised machine learning to studyin situbehavior of the medusaChrysaora fuscescens

2019 ◽  
Author(s):  
Clara Fannjiang ◽  
T. Aran Mooney ◽  
Seth Cones ◽  
David Mann ◽  
K. Alex Shorter ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
Laboratory Data ◽  
Supervised Machine Learning ◽  
Motion Sensors ◽  
Fine Scale ◽  
Video Footage ◽  
Research Findings ◽  
Summary Statement

AbstractZooplankton occupy critical roles in marine ecosystems, yet their fine-scale behavior remains poorly understood due to the difficulty of studying individualsin situ. Here we combine biologging with supervised machine learning (ML) to demonstrate a pipeline for studyingin situbehavior of larger zooplankton such as jellyfish. We deployed the ITAG, a biologging package with high-resolution motion sensors designed for soft-bodied invertebrates, on 8Chrysaora fuscescensin Monterey Bay, using the tether method for retrieval. Using simultaneous video footage of the tagged jellyfish, we develop ML methods to 1) identify periods of tag data corrupted by the tether method, which may have compromised prior research findings, and 2) classify jellyfish behaviors. Our tools yield characterizations of fine-scale jellyfish activity and orientation over long durations, and provide evidence that developing behavioral classifiers onin siturather than laboratory data is essential.Summary StatementHigh-resolution motion sensors paired with supervised machine learning can be used to infer fine-scalein situbehavior of zooplankton for long durations.

scholarly journals A New Land Surface Hydrology within the Noah-WRF Land-Atmosphere Mesoscale Model Applied to Semiarid Environment: Evaluation over the Dantiandou Kori (Niger)

2009 ◽  
Vol 2009 ◽  
pp. 1-13 ◽  
Author(s):  
B. Decharme ◽  
C. Ottlé ◽  
S. Saux-Picart ◽  
N. Boulain ◽  
B. Cappelaere ◽  
...  
Keyword(s):  
Land Surface ◽  
Mesoscale Model ◽  
West African Monsoon ◽  
Radar Data ◽  
Rain Gauge ◽  
Surface Energy Budget ◽  
Surface Hydrology ◽  
Land Surface Hydrology ◽  
Rain Gauge Network

Land-atmosphere feedbacks, which are particularly important over the Sahel during the West African Monsoon (WAM), partly depend on a large range of processes linked to the land surface hydrology and the vegetation heterogeneities. This study focuses on the evaluation of a new land surface hydrology within the Noah-WRF land-atmosphere-coupled mesoscale model over the Sahel. This new hydrology explicitly takes account for the Dunne runoff using topographic information, the Horton runoff using a Green-Ampt approximation, and land surface heterogeneities. The previous and new versions of Noah-WRF are compared against a unique observation dataset located over the Dantiandou Kori (Niger). This dataset includes dense rain gauge network, surfaces temperatures estimated from MSG/SEVIRI data, surface soil moisture mapping based on ASAR/ENVISAT C-band radar data and in situ observations of surface atmospheric and land surface energy budget variables. Generally, the WAM is reasonably reproduced by Noah-WRF even if some limitations appear throughout the comparison between simulations and observations. An appreciable improvement of the model results is also found when the new hydrology is used. This fact seems to emphasize the relative importance of the representation of the land surface hydrological processes on the WAM simulated by Noah-WRF over the Sahel.

Analysis of the World's First Polymer Injectivity Test in a Carbonate Reservoir Under Extreme Harsh Conditions in ADNOC's Reservoirs

2021 ◽  
Author(s):  
Juan Manuel Leon ◽  
Shehadeh K. Masalmeh ◽  
Siqing Xu ◽  
Ali M. AlSumaiti ◽  
Ahmed A. BinAmro ◽  
...  
Keyword(s):  
High Temperature ◽  
Laboratory Experiments ◽  
High Salinity ◽  
Laboratory Data ◽  
Injection Pressure ◽  
Carbonate Reservoir ◽  
Experimental Program ◽  
Full Field ◽  
Harsh Conditions

Abstract Assessing polymer injectivity for EOR field applications is highly important and challenging. An excessive injectivity reduction during and after polymer injection may potentially affect the well integrity and recovery efficiency and consequently, injection strategy and the economics of the polymer projects. Moreover, well conditions such as skin, completion configuration, and injection water quality can significantly impact polymer injectivity. Additionally, the presence of fractures or micro-fractures may govern injection pressure. In contrast, historic field applications have shown that polymer injectivity is in general better than expected from simulations or laboratory data. In the laboratory experiments, the polymer injectivity has been evaluated by injection of significant amounts of pore volumes of polymer at relevant well-injection rates. In addition, several experiments were performed to measure the complex in-situ rheology expected to dominate the flow near the wellbore This paper presents the analysis of the the world's first polymer injectivity test (PIT) conducted in a high temperature and high salinity (HTHS) carbonate reservoir in Abu Dhabi as part of a comprehensive de-risking program for a new polymer-based EOR scheme proposed by ADNOC for these challenging carbonate reservoirs (see Masalmeh et. al., 2014). The de-risking program includes an extensive laboratory experimental program and field injectivity test to ensure that the identified polymer can be injected and propagated in the target formation before multi-well pilot and full-field implementation stages. Experimental laboratory data and the field injectivity test results are presented in earlier publications (Masalmeh et. al., 2019; Rachapudi et. al., 2020) and references therein. This PIT is the world's first polymer injectivity test in a carbonate reservoir under such harsh conditions of high salinity, high content of divalent ions and high temperature. In addition, the polymer used during the test has never been field-tested before. Therefore, the results of the PIT interpretation will help to de-risk the suitable polymer for the future inter-well pilot for the new proposed EOR Polymer-based scheme and it is a game-changer to unlock several opportunities for different Chemical EOR applications on full-field scale in other reservoirs with similar characteristics. A single well radial simulation model was built to integrate the surveillance data during PIT and the extensive laboratory experiments. Morever, multiple Pressure Fall Off Tests (PFOs) during the same periods were analyzed and intergaretd in the model.The study assessed the effect of polymer viscosity on mobility reduction, evaluated the polymer bank propagation, investigated the effect of the skin build-up, residual resistance factor (RRF) and shear effects on the well injectivity. Additionally, a comprehensive assisted history match method and robust simulation sensitivity analysis was implemented, thousands of sensitivity simulation runs were performed to capture several possible injection scenarios and validate laboratory parameters. The simulation study confirmed that the PIT could be interpreted using the laboratory-measured polymer parameters such as polymer bulk viscosity, in-situ rheology, RRF and adsorption.

scholarly journals Exploring Deep-Rock Mechanics through Mechanical Analysis of Hard-Rock In Situ Coring System

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Jianan Li ◽  
Heping Xie ◽  
Ling Chen ◽  
Cong Li ◽  
Zhiqiang He
Keyword(s):  
Rock Mechanics ◽  
Hard Rock ◽  
Design Method ◽  
Drill Pipe ◽  
In Situ Stress ◽  
Drilling Depth ◽  
Innovative Design ◽  
The Core ◽  
Deep Rock

Exploration of deep-rock mechanics has a significant influence on the techniques of mining and rock mechanics. Rock coring technique is the basic method for all rock mechanics study. With the increase of the drilling depth and increasing strength of the hard rock, how to obtain high-quality rock core through various coring techniques is an eternal work. Here an innovative method is applied to design the new coring system to maximize the efficiency of operation. The stress conditions or parameters of rock core in the coring are analyzed, and the mechanism of the core with in situ stress is shown in this paper. The conflict of the core and coring tool chamber is proposed for the innovative design. The innovative design method is fulfilled by the theory of inventive problem solving (TRIZ). An improved coring system for the full-length core with in situ stress was obtained with the solutions of improved coring mechanism, cutting mechanism, and spiral drill pipe.

scholarly journals Comparison of large-scale Birkeland currents determined from Iridium and SuperDARN data

2006 ◽  
Vol 24 (3) ◽  
pp. 941-959 ◽  
Author(s):  
D. L. Green ◽  
C. L. Waters ◽  
B. J. Anderson ◽  
H. Korth ◽  
R. J. Barnes
Keyword(s):  
Electric Field ◽  
Large Scale ◽  
Radar Data ◽  
Space Environment ◽  
Near Earth Space ◽  
Radar Network ◽  
High Latitude Ionosphere ◽  
Ionospheric Electric Field ◽  
Birkeland Currents

Abstract. The Birkeland currents, J||, electrically couple the high latitude ionosphere with the near Earth space environment. Approximating the spatial distribution of the Birkeland currents may be achieved using the divergence of the ionospheric electric field, , assuming zero conductance gradients such that . In this paper, electric field data derived from the Super Dual Auroral Radar Network (SuperDARN) are used to calculate , which is compared with the Birkeland current distribution derived globally from the constellation of Iridium satellites poleward of 60° magnetic latitude. We find that the assumption of zero conductance gradients is often a poor approximation. On the dayside, in regions where the SuperDARN electric field is constrained by radar returns, the agreement in the locations of regions of upward and downward current between and J|| obtained from Iridium data is reasonable with differences of less than 3° in the latitudinal location of major current features. It is also shown that away from noon, currents arising from conductance gradients can be larger than the component. By combining the estimate in regions of radar coverage with in-situ estimates of conductance gradients from DMSP satellite particle data, the agreement with the Iridium derived J|| is considerably improved. However, using an empirical model of ionospheric conductance did not account for the conductance gradient current terms. In regions where radar data are sparse or non-existent and therefore constrained by the statistical potential model the approximation does not agree with J|| calculated from Iridium data.

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