Pycaro's instrument proof of concept

Carreño-Luengo, Hugo; Camps, A.; Perez-Ramos, I.; Rius, A.

doi:10.1109/gnssr.2012.6408251

Cited by 6 publications

(13 citation statements)

References 12 publications

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“…To overcome some limitations of the previous techniques, newer approaches have been developed, namely, the reconstructed GNSS-R (rGNSS-R) [124]- [126] and the partial interferometric GNSS-R (piGNSS-R) [127]. The rGNSS-R is similar to the cGNSS-R technique, but semicodeless techniques are used to reconstruct the P(Y) code which is then correlated with the reflected signal.…”

Section: Local Codementioning

confidence: 99%

“…Its launch is scheduled for the end of 2015 [55], [56]. 3 Cat-2's main payload is PYCARO: the P(Y) and C/A Re-flectOmeter [124]. It includes two receiving channels, and two dual-frequency (L1+L2) and dual-polarization (switchable) antennas: the zenithal antenna, a single microstrip patch, and the nadir-looking antenna, a 3 # 2 array of microstrip patches with +13 dB gain.…”

Section: B Cygnssmentioning

confidence: 99%

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Tutorial on Remote Sensing Using GNSS Bistatic Radar of Opportunity

Zavorotny

Gleason²,

Cardellach³

et al. 2014

IEEE Geosci. Remote Sens. Mag.

440

290

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In traditional GNSS applications, signals arriving at a receiver's antenna from nearby reflecting surfaces (multipath) interfere with the signals received directly from the satellites which can often result in a reduction of positioning accuracy. About two decades ago researchers produced an idea to use reflected GNSS signals for remote-sensing applications. In this new concept a GNSS transmitter together with a receiver capable of processing GNSS scattered signals of opportunity becomes bistatic radar. By properly processing the scattered signal, this system can be configured either as an altimeter, or a scatterometer allowing us to estimate such characteristics of land or ocean surface as height, roughness, or dielectric properties of the underlying media. From there, using various methods the geophysical parameters can be estimated such as mesoscale ocean topography, ocean surface winds, soil moisture, vegetation, snowpack, and sea ice. Depending on the platform of the GNSS receiver (stationary, airborne, or spaceborne), the capabilities of this technique and specific methods for processing of the reflected signals may vary. In this tutorial, we describe this new remotesensing technique, discuss some of the interesting results that have been already obtained, and give an overview of current and planned spacecraft missions.

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Section: Local Codementioning

confidence: 99%

Section: B Cygnssmentioning

confidence: 99%

Tutorial on Remote Sensing Using GNSS Bistatic Radar of Opportunity

Zavorotny

Gleason²,

Cardellach³

et al. 2014

IEEE Geosci. Remote Sens. Mag.

440

290

View full text Add to dashboard Cite

show abstract

“…3. As a combination of the previous two methods, dual fr equency GNSS-R receivers can use the so-called codeless technique to estimate the P-code, which is present in the L I and L2 band simultaneously, and use it as in conventional GNSS-R to achieve higher resolution and better SNR [12]. 4.…”

Section: B Te Chniquesmentioning

confidence: 99%

Land monitoring using GNSS-R techniques: A review of recent advances

Camps

Rodriguez-Alvarez

Valencia

et al. 2013

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS

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Soil moisture is required to improve meteorological and climate predictions. Global soil moisture maps are nowadays produced daily from SMOS satellite data, with a basic spatial resolution of -50 km. Recently, using data fu sion techniques between SMOS and MODIS data, an operational service has been implemented at the SMOS Barcelona Expert Center to downscale SMOS data down to 1 km over the Iberian peninsula [11. However, despite SMOS operates in the passive microwave "protected" band from 1400 to 1427 MHz, radio fre quency interference may degrade the quality of the soil moisture (and sea salinity) retrievals or even prevent them [21. Signals of opportunity transmitted from Global Navigation Satellite Systems (GNSS) can be used for soil moisture, vegetation, snow, water level. .. monitoring after reflection (GNSS-R) on the Earth's surface. In principle, eventhough these signals can also be jammed, their structure and the way they are processed, makes them more robust in front of radio-frequency interference, while at the same time -in principle-can achieve also a better spatial resolution. In this work, the few different GNSS-R techniques are first revised, including their pros and cons. Then a few applications are revised, with special emphasis -but not exclusively-in those in which the UPC Remote Sensing Lab has been working.

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“…According to the research and demonstration mission planned by the Remote Sensing Lab and the NanoSat Lab at the Universitat Politècnica de Catalunya-Barcelona Tech, PYCARO will be carried on a 3 Â 2 unit Cube satellite to perform the observation of Earth surface and atmosphere. Compared to the receivers above, the difference of PYCARO is a P(Y) and C/A ReflectOmeter, which adds the processing of encrypted L1 and L2 P(Y) signals by using semicodeless technique [36,37]. The zenith antenna of PYCARO is a single microstrip patch, and the nadir-looking antenna is a 3 Â 2 array of microstrip patches with 13 dB gain.…”

Section: Pycaromentioning

confidence: 99%

GNSS Application in Retrieving Sea Wind Speed

Yang¹,

Wang²

2018

Multifunctional Operation and Application of GPS

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In traditional Global Navigation Satellite System (GNSS) application, the reflected GNSS signals from Earth's surface generally are considered as an interference source to be suppressed or removed. Recently, a new idea which treats the reflected GNSS signal as opportunity source of remote sensing has been proposed to monitor Earth's physical parameters. This technique is called as GNSS-Reflectometry (GNSS-R) which has the advantages of low-power,-mass and-cost. With the development and modernization of GPS, Galileo, GLONASS, and BeiDou system, spaceborne GNSS could significantly improve the temporal-spatial resolution by receiving and processing the reflected signal from multiple satellites. This chapter mainly describes this new bi-static remote sensing technique. First, basic theories of GNSS-R including spatial geometry, polarization, and scattering model of reflected signal are discussed; second, spaceborne receivers and fastresponse processing methods are reviewed and analyzed; finally, the empirical models retrieving wind speed are proposed and demonstrated using the DDM data from the UK-TechDomeSat-1 satellite. Based on the discussion of this chapter, it could be concluded that although GNSS-R still has some key challenges which have to be addressed, it could be an optimal choice of remote sensing in some special conditions, such as the tropical cyclone.

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Pycaro's instrument proof of concept

Cited by 6 publications

References 12 publications

Tutorial on Remote Sensing Using GNSS Bistatic Radar of Opportunity

Tutorial on Remote Sensing Using GNSS Bistatic Radar of Opportunity

Land monitoring using GNSS-R techniques: A review of recent advances

GNSS Application in Retrieving Sea Wind Speed

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