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literature.bib
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@article{Zavorotny2013,
author = {Zavorotny, Valery U and Rodriguez-alvarez, Nereida and Akos, Dennis M and Smith, Jeffrey A and Camps, Adriano and Fairall, Christopher W},
doi = {10.1109/TGRS.2012.2196437},
file = {:Users/rgaehwiler/Documents/TTU/4th term/Thesis/Papers/06208860.pdf:pdf},
number = {January 2016},
pages = {626--641},
title = {{Airborne GNSS-R wind retrievals using delay- Doppler maps Airborne GNSS-R Wind Retrievals Using Delay – Doppler Maps}},
volume = {51},
year = {2013}
}
@techreport{Hobiger2014,
abstract = {Master Thesis Proposal for GNSS-R with a SDR},
author = {Hobiger, Thomas},
file = {:Users/rgaehwiler/Documents/TTU/4th term/ChalmersHobiger/SEE_Master_thesis_project_GNSS-R-receiver.pdf:pdf},
keywords = {gnssr,hobiger,proposal,sdr,thesis,thomas},
mendeley-tags = {gnssr,proposal,sdr,thesis},
title = {{Development a versatile GNSS-R receiver by means of software defined radio}},
year = {2017}
}
@misc{altimet,
author = {Esa and Cnes},
keywords = {altimetry,cnes,esa},
mendeley-tags = {altimetry,esa},
title = {{Radar Altimetry - Tutorial & Toolbox}},
url = {www.altimetry.info},
urldate = {2018-03-03}
}
@misc{limewiki,
author = {Myriadrf},
keywords = {limesdr,myriadrf,wiki},
mendeley-tags = {limesdr,myriadrf,wiki},
title = {{LimeSDR Wiki}},
url = {https://wiki.myriadrf.org/LimeSDR},
urldate = {2018-02-11}
}
@misc{CSIC,
abstract = {Institute of Space Sciences, CSIC of the Spanish National Research Council. GNSS-R experimental data and information.},
author = {CISC},
keywords = {csic,ddm,raw data},
mendeley-tags = {ddm,raw data},
title = {{Gold RTR Mining}},
url = {https://www.ice.csic.es/research/gold_rtr_mining/index.php},
urldate = {2018-04-28}
}
@misc{limeapi,
abstract = {Description of LimeSDR Aplication Programmers Interface.},
author = {Myriadrf},
keywords = {api,doxygen,driver,limesdr,limesuite,myriadrf,software,sw},
mendeley-tags = {api,doxygen,driver,limesdr,limesuite,myriadrf,software,sw},
title = {{LMS API Documentation}},
url = {http://docs.myriadrf.org/LMS_API/index.html},
urldate = {2018-03-03},
year = {2017}
}
@inproceedings{dbzp,
abstract = {An important observation of GNSS-R is Delay-Doppler mapping (DDM). According to the requirement of GNSS-R signal real-time processing, a fast processing algorithm of GNSS-R signal based on double block zero padding (DBZP) and frequency domain rotation transformation is proposed for DDM generation. The reflected data is blocked and then correlated, which avoids the FFT calculation with too long points. The block and zero padding operations not only guarantee the full search of the pseudo code phase, but also avoid the repetitive calculation. In the frequency domain, the correlation results at different Doppler frequencies are approximated by the rotation transformation method, which avoids a large number of carrier multiplication operations and effectively reduces the computational burden. The computational burden and computational loss of parallel code phase correlation algorithm and fast algorithm are analyzed. Finally, the simulation time-consuming and processing results were compared. The results show that the fast algorithm greatly shortens the DDM generation time and the loss ofthe processing result is small.},
author = {Han, Lin and Meng, Yansong and Wang, Yanguang and Han, Xingyuan},
booktitle = {China Satellite Navigation Conference 2017},
keywords = {gnss-r,gnssr,reflectometry},
mendeley-tags = {gnss-r,gnssr,reflectometry},
publisher = {Springer Nature Singapore},
title = {{A Fast Algorithm of GNSS-R Signal Processing Based on DBZP}},
year = {2017}
}
@misc{nasajpl,
abstract = {Introduction into scatterometry and the history.},
author = {NASA, JPL},
keywords = {history,jpl,nasa,scatterometry},
mendeley-tags = {history,jpl,nasa,scatterometry},
title = {{NASA - Jet Propulsion Laboratory - Scatterometry}},
url = {https://winds.jpl.nasa.gov/aboutscatterometry/history/},
urldate = {2018-04-29}
}
@article{Gleason2015,
abstract = {The CYGNSS satellite constellation consists of eight satellites equipped with GNSS bi-static radar receivers which map the ocean surface scattered signal power in the vicinity of the specular reflection point using time domain and Doppler frequency filters. The satellites orbit in the same plane at an altitude of 500 km and at a orbit inclination of 35 degrees. CYGNSS will act as a GNSS bi-static scatterometer capable of sensing sea level winds in tropical cyclones, including in high precipitation conditions. An overview of the GNSS remote sensing concept is included in this paper. Subsequently, an overview of the Delay Doppler Mapping Instrument (DDMI) carried by all of the CYGNSS observatories will be presented. The DDMI uses GPS forward scattered signals of opportunity to produce delay Doppler maps (DDMs) of the scattered signal delay and frequency spreading over the surface. This paper will conclude with results from preliminary laboratory testing of the CYGNSS instrument engineering models.},
author = {Gleason, Scott and Ruf, Christopher},
doi = {10.1109/MWSYM.2015.7166775},
file = {:Users/rgaehwiler/Documents/TTU/4th term/Thesis/Papers/IMS2015_Gleason-and-Ruf_DDMI-for-CYGNSS.pdf:pdf},
isbn = {9781479982752},
issn = {0149-645X},
journal = {2015 IEEE MTT-S International Microwave Symposium, IMS 2015},
keywords = {Bistatic Radar,CYGNSS,Calibration,GNSS,GPS,Instruments,Reflectometry,Scatterometry},
number = {Ddmi},
pages = {2--5},
title = {{Overview of the Delay Doppler Mapping Instrument (DDMI) for the cyclone global navigation satellite systems mission (CYGNSS)}},
year = {2015}
}
@article{Komjathy2004,
abstract = {Global positioning system (GPS) signals reflected from the ocean surface can be used for various remote sensing purposes. Some possibilities include measurements of surface roughness characteristics from which the rms of wave slopes, wind speed, and direction could be determined. In this paper, reflected GPS measurements that were collected using aircraft with a delay mapping GPS receiver are used to explore the possibility of determining ocean surface wind speed and direction during flights to Hurricanes Michael and Keith in October 2000. To interpret the GPS data, a theoretical model is used to describe the correlation power of the reflected GPS signals for different time delays as a function of geometrical and sea-roughness parameters. The model employs a simple relationship between surface-slope statistics and both a wind vector and wave age or fetch. Therefore, for situations when this relationship holds there is a possibility of indirectly measuring the wind speed and the wind direction. Wind direction estimates are based on a multiple-satellite nonlinear least squares solution. The estimated wind speed using surface-reflected GPS data collected at wind speeds between 5 and 10 m s−1 shows an overall agreement of better than 2 m s−1 with data obtained from nearby buoy data and independent wind speed measurements derived from TOPEX/Poseidon, European Remote Sensing (ERS), and QuikSCAT observations. GPS wind retrievals for strong winds in the close vicinity to and inside the hurricane are significantly less accurate. Wind direction agreement with QuikSCAT measurements appears to be at the 30° level when the airplane has both a stable flight level and a stable flight direction. Discrepancies between GPS retrieved wind speeds/directions and those obtained by other means are discussed and possible explanations are proposed.},
author = {Komjathy, Attila and Armatys, Michael and Masters, Dallas and Axelrad, Penina and Zavorotny, Valery and Katzberg, Steven},
doi = {10.1175/1520-0426(2004)021<0515:ROOSWS>2.0.CO;2},
isbn = {0739-0572},
issn = {0739-0572},
journal = {Journal of Atmospheric and Oceanic Technology},
pages = {515--526},
title = {{Retrieval of Ocean Surface Wind Speed and Wind Direction Using Reflected GPS Signals}},
volume = {21},
year = {2004}
}
@misc{limegit,
abstract = {Opensource Repository for the LimeSuite and LimeSDR Ecosystem},
author = {Myriadrf},
keywords = {git,github,limesdr,limesuite,myriad,myriadrf,open source,opensource,repo,repository,schematic,software},
mendeley-tags = {github,limesdr,limesuite,myriad,myriadrf,open source,opensource,repo,repository,schematic,software},
title = {{Myriad-RF GitHub Repository}},
urldate = {2018-03-03}
}
@book{gnsshandbook,
author = {Teunissen, Peter J. G. and Montenbruck, Oliver},
isbn = {978-3-319-42926-7},
keywords = {GNSS,GPS},
pages = {1325},
publisher = {Springer},
title = {{Springer Handbook of Global Navigation Satellite Systems}},
year = {2017}
}
@article{Lowe2002,
author = {Lowe, Stephen T and Kroger, Peter and Franklin, Garth and Labrecque, John L and Lerma, Jesse and Lough, Michael and Marcin, Martin R and Muellerschoen, Ronald J and Spitzmesser, Donovan and Young, Larry E},
file = {:Users/rgaehwiler/Documents/TTU/4th term/Thesis/Papers/01010901.pdf:pdf},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
number = {5},
pages = {1150--1163},
title = {{A Delay / Doppler-Mapping Receiver System for GPS-Reflection Remote Sensing}},
volume = {40},
year = {2002}
}
@article{Harmon1999,
abstract = {Mars radar imaging results from Arecibo 12.6-cm observations are presented. The images were derived from delay-Doppler mapping using a coded-long-pulse technique to mitigate the effects of echo overspreading. Images of the depolarized echo are used to identify regions of high decimeter-scale roughness. Some of the strongest echo features are located on the major shield volcanoes or on relatively young off-shield flows such as the Olympus and Pavonis lava aprons. The shields themselves have highly irregular radar signatures suggesting complex volcanic histories. Some Mars radar features have twice the depolarized brightness of the roughest terrestrial lava flows, apparently due to higher levels of multiple scattering from surfaces of spectacular roughness or from volume scattering. Low-brightness (smooth) areas are associated with older surfaces such as fractured and highland terra, as well as with terrain interpreted to be debris lobes, ash flows, and aureoles; in particular, a close connection was found between the 12.6-cm counterpart of the "Stealth" feature and the Medusae Fossae Formation (postulated to be deep ignimbrite deposits). Marte Vallis is anomalous in being the only outflow channel showing strongly enhanced echoes, which supports the idea that this channel and the Elysium Basin that it drained are filled with lava flows. A weak radar feature was found for the south polar residual ice cap. Comparisons with Goldstone 3.5-cm data show that the south polar enhancement is much weaker at 12.6 cm than at 3.5 cm, indicating that the southern ice cap becomes optically thin at the longer wavelength. A north polar enhancement has also been found, which is comparable in strength to the 12.6-cm south polar feature.},
author = {Harmon, J K and Arvidson, R E and Guinness, E A and Campbell, B A and Slade, M A},
doi = {Doi 10.1029/1998je900042},
isbn = {0148-0227},
issn = {0148-0227},
journal = {Journal of Geophysical Research-Planets},
keywords = {backscatter,callisto,ganymede,ice,images,mercury radar,polar anomalies,region,satellites,topography},
number = {E6},
pages = {14065--14089},
title = {{Mars mapping with delay-Doppler radar}},
volume = {104},
year = {1999}
}
@article{Martin-Neira1993,
abstract = {To date, altimetry from space has mainly been limited to nadir-looking-type instruments because of the difficulty of realising a precise wide-swath radar altimeter. A concept is presented that can be used to perform altimetry measurements over points along directions other than nadir, by making use of a passive instrument. The method is applied here to ocean altimetry in particular. This concept, based on the existence of sources of opportunity, consists of combining the direct signal and the signal that is reflected by the Earth's surface to obtain the desired measurement. It can be regarded as a multistatic radar for which the transmitters and the receivers belong to different systems. Because of the combination of direct and reflected signals, this concept has been called the "Passive Reflectometry and Interferometric System' (PARIS).},
author = {Martin-Neira, M.},
issn = {03792285},
journal = {ESA journal},
number = {4},
pages = {331--355},
title = {{A Passive Reflectometry and Interferometry System(PARIS)- Application to ocean altimetry}},
volume = {17},
year = {1993}
}
@article{Zavorotny2000,
abstract = {A theoretical model that describes the power of a scattered Global Positioning System (GPS) signal as a function of geometrical and environmental parameters has been developed. This model is based on a bistatic radar equation derived using the geometric optics limit of the Kirchhoff approximation. The waveform (i.e., the time-delayed power obtained in the delay-mapping technique) depends on a wave-slope probability density function, which in turn depends on wind. Waveforms obtained for aircraft altitudes and velocities indicate that altitudes within the interval 5-15 km are the best for inferring wind speed. In some regimes, an analytical solution for the bistatic radar equation is possible. This solution allows converting trailing edges of waveforms into a set of straight lines, which could be convenient for wind retrieval. A transition to satellite altitudes, together with satellite velocities, makes the peak power reduction and the Doppler spreading effect a significant problem for wind retrieval based on the delay-mapping technique. At the same time, different time delays and different Doppler shifts of the scattered GPS signal could form relatively small spatial cells on sea surface, suggesting mapping of the wave-slope probability distribution in a synthetic-aperture-radar (SAR) fashion. This may allow more accurate measurements of wind velocity and wind direction},
author = {Zavorotny, Valery U. and Voronovich, Alexander G.},
doi = {10.1109/36.841977},
file = {:Users/rgaehwiler/Library/Application Support/Mendeley Desktop/Downloaded/Zavorotny, Voronovich - 2000 - Scattering of GPS signals from the ocean with wind remote sensing application(2).pdf:pdf},
isbn = {0196-2892},
issn = {01962892},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
number = {2 II},
pages = {951--964},
title = {{Scattering of GPS signals from the ocean with wind remote sensing application}},
volume = {38},
year = {2000}
}
@article{Hobiger2014a,
author = {Hobiger, T. and Haas, R. and L{\"{o}}fgren, J. S.},
doi = {10.1002/2013RS005359},
file = {:Users/rgaehwiler/Documents/TTU/4th term/ChalmersHobiger/ThesisPublications/Hobiger_et_al-2014-Radio_Science.pdf:pdf},
issn = {00486604},
journal = {Radio Science},
keywords = {fdma,glonass,gnssr,haas,hobiger},
mendeley-tags = {fdma,glonass,gnssr},
pages = {n/a--n/a},
title = {{GLONASS-R: GNSS reflectometry with an FDMA based satellite navigation system}},
url = {http://doi.wiley.com/10.1002/2013RS005359},
year = {2014}
}
@article{Wickert2016,
abstract = {GEROS-ISS (GEROS hereafter) stands for GNSS REflectometry, Radio Occultation and Scatterometry onboard the International Space Station. It is a scientific experiment, proposed to the European Space Agency (ESA) in 2011 for installation aboard the ISS. The main focus of GEROS is the dedicated use of signals from the currently available Global Navigation Satellite Systems (GNSS) for remote sensing of the System Earth with focus to Climate Change characterisation. The GEROS mission idea and the current status are briefly reviewed.},
author = {Wickert, Jens and Cardellach, Estel and Martin-Neira, Manuel and Bandeiras, Jorge and Bertino, Laurent and Andersen, Ole Baltazar and Camps, Adriano and Catarino, Nuno and Chapron, Bertrand and Fabra, Fran and Floury, Nicolas and Foti, Giuseppe and Gommenginger, Christine and Hatton, Jason and Hoeg, Per and Jaggi, Adrian and Kern, Michael and Lee, Tong and Li, Zhijin and Park, Hyuk and Pierdicca, Nazzareno and Ressler, Gerhard and Rius, Antonio and Rosello, Josep and Saynisch, Jan and Soulat, Francois and Shum, C. K. and Semmling, Maximilian and Sousa, Ana and Xie, Jiping and Zuffada, Cinzia},
doi = {10.1109/JSTARS.2016.2614428},
isbn = {1939-1404 VO - 9},
issn = {21511535},
journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
keywords = {GNSS radio occultation,Global Navigation Satellite Systems (GNSS) reflect,international space station,mean sea level,mesoscale ocean currents},
number = {10},
pages = {4552--4581},
title = {{GEROS-ISS: GNSS REflectometry, Radio Occultation, and Scatterometry Onboard the International Space Station}},
volume = {9},
year = {2016}
}
@book{Ruf2016,
abstract = {Deriving Surface Wind Speeds in Tropical Cyclones},
author = {Ruf, C. and Clarizia, M.P. and Gleason, S. and Jelenak, Z. and Murray, J. and Morris, M. and Musko, S. and Posselt, D. and Provost, D. and Starkenburg, D. and Zavorotny, V.},
file = {:Users/rgaehwiler/Documents/TTU/4th term/Thesis/Papers/CYGNSS_Handbook_April2016.pdf:pdf},
isbn = {978-1-60785-380-0},
keywords = {cyclone,ddm,handbook,nasa,ruf},
mendeley-tags = {cyclone,ddm,handbook,nasa},
title = {{CYGNSS Handbook - Cyclone Global Navigation Satellite System}},
year = {2016}
}
@unpublished{lms7002,
abstract = {SUMMARY FEATURES * Field Programmable Radio Frequency (FPRF) chip * Dual transceiver ideal for MIMO * User programmable on the fly * Continuous coverage of the 100 kHz -3.8 GHz RF frequency range * Digital interface to baseband with on chip integrated 12 bit D/A and A/D converters * Programmable RF modulation bandwidth up to 160 MHz using analog interface * Programmable RF modulation bandwidth up to 60 MHz using digital interface * Supports both TDD and full duplex FDD * LimeLight™ digital IQ interface – JEDEC JESD207 TDD and FDD compliant * Transceiver Signal Processor block employs advanced techniques for enhanced performance * Single chip supports 2x2 MIMO. Multiple chips can be used to implement higher order MIMO * On-chip RF calibration circuitry * Fully differential baseband signals, analog IQ * Few external components},
author = {{Lime Microsystems}},
file = {:Users/rgaehwiler/Documents/PapersBooksManuals/@Datasheets/MyriadRf-LimeSDR/LMS7002M_Data_Sheet_v3.1r00.pdf:pdf},
keywords = {limesdr,lms7002m,myriadrf,sdr,software defined radio,sw},
mendeley-tags = {limesdr,lms7002m,myriadrf,sdr,software defined radio,sw},
pages = {27},
title = {{LMS7002M - FPRF MIMO Transceiver IC With Integrated Microcontroller}},
url = {https://github.com/myriadrf/LMS7002M-docs},
year = {2015}
}