Application of the ICF Coherence Time Method for Ocean Remote Sensing Using Digital Communication Satellite Signals

Shah, Rashmi; Garrison, James L.

doi:10.1109/jstars.2014.2314531

Cited by 25 publications

(12 citation statements)

References 14 publications

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“…In our study, for the sake of simplicity in the analysis, the feedback channel carrying CSI information is assumed to be reliable 1 . In addition, the temporal coherence times of considered FSO [36] and RF [37] links, i.e., in the order of tens of milliseconds, are relatively long in comparison with the time slot duration, including the data transmission and feedback time (order of several milliseconds). Due to the slowly time-varying nature of fading channels, CSIs are still up-to-date information when arriving at the HAP and satellite.…”

Section: A Adaptive Transmission Schemesmentioning

confidence: 99%

On the Design of Rate Adaptation for Relay-Assisted Satellite Hybrid FSO/RF Systems

Nguyen

Dang

et al. 2022

IEEE Photonics J.

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This paper addresses the design of hybrid freespace optical/radio frequency (FSO/RF) systems for a highaltitude platform (HAP)-aided relaying satellite communication for mobile networks supported by unmanned aerial vehicle (UAV). While prior work primarily focused on fixed-rate design, which frequently switches between FSO and RF lead reduced the system performance, we propose a rate adaptation design that gradually adjusts the data rate in each link when its channel state fluctuates, under a target bit error rate (BER) constraint. The proposed design's downlink performance is analyzed, taking into account many challenging issues, including beam spreading loss, cloud attenuation, statistical behaviors of the atmospheric turbulence in the dual-hop channel, and pointing misalignment due to the UAV hovering. Different performance metrics are analytically derived based on channel modelings, including outage probability, average transmission rate, and achievable spectrum efficiency. In addition, the average system BER, which satisfies the design constraint, is also numerically obtained. The results quantitatively confirm the effectiveness of our proposed system under the impact of UAV hovering misalignment and atmospheric-related issues like clouds and turbulence. Finally, Monte-Carlo simulations validate the accuracy of theoretical results.

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Section: A Adaptive Transmission Schemesmentioning

confidence: 99%

On the Design of Rate Adaptation for Relay-Assisted Satellite Hybrid FSO/RF Systems

Nguyen

Dang

et al. 2022

IEEE Photonics J.

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“…In theory, all of the above-listed GNSS constellations, as well as numerous other signals of opportunity not discussed in this tutorial (see [62]- [64] for examples of using non-GNSS signals for bistatic remote sensing) can be used for Earth remote sensing. One of the most attractive benefits of GNSS-R is its general simplicity and low-cost passive instrumentation, which enables smaller instruments, smaller satellites, and larger constellations.…”

Section: B Gnss-r Coverage and Revisit Timementioning

confidence: 99%

Tutorial on Remote Sensing Using GNSS Bistatic Radar of Opportunity

Zavorotny

Gleason²,

Cardellach³

et al. 2014

IEEE Geosci. Remote Sens. Mag.

434

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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“…Where 𝐴 𝑑 2 and 𝐴 𝑟 2 are the direct signal power and the reflected signal power, respectively, and 𝜙 𝛾 is the phase delay between the direct signal and the reflected signal. According to Fig 1, 𝜙 𝛾 can be expressed as : 4 sin…”

Section: Basic Principle Of Gnss-ir Modelmentioning

confidence: 99%

“…that has been gradually developed since the 1990's and is one of the research hot spots in the field of remote sensing detection and navigation technology [1]. Since the discovery of the surface reflection signal, which was originally a source of multipath error, can be used as a new type of remote sensing signal source for the inversion of the characteristic parameters of the surface reflection surface, many scholars launched the research on GNSS-R signal [2][3][4][5]. At present, the research of sea level height measurement based on reflected signal mainly includes phase delay analysis method [6][7][8][9], and SNR analysis method.…”

Section: Introductionmentioning

confidence: 99%

GNSS-IR Model of Sea Level Height Estimation Combining Variational Mode Decomposition

Hu¹,

Yuan²,

Liu³

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The Global Navigation Satellite System-Reflections (GNSS-R) signal has been confirmed to be useful for retrieving sea level height. At present, the GNSS-Interferometric Reflectometry (GNSS-IR) technology based on the least square method to process signal-to-noise ratio (SNR) data is restricted by the satellite elevation angle in terms of accuracy and stability. This paper proposes a new GNSS-IR model combining variational mode decomposition (VMD) for sea level height estimation. VMD is used to decompose the SNR data into intrinsic mode functions (IMF) of layers with different frequencies, remove the IMF representing the trend item of the SNR data, and reconstruct the remaining IMF components to obtain the SNR oscillation item. In order to verify the validity of the new GNSS-IR model, the measurement data provided by the Onsala Space Observatory in Sweden is used to evaluate the performance of the algorithm and its stability in high elevation range. The experimental results show that the VMD method has good results in terms of accuracy and stability, and has advantages compared to other methods. For the half-year GNSS SNR data, the root mean square error (RMSE) and correlation coefficient of the new model based on the VMD method are 4.86 cm and 0.97, respectively.

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Application of the ICF Coherence Time Method for Ocean Remote Sensing Using Digital Communication Satellite Signals

Cited by 25 publications

References 14 publications

On the Design of Rate Adaptation for Relay-Assisted Satellite Hybrid FSO/RF Systems

On the Design of Rate Adaptation for Relay-Assisted Satellite Hybrid FSO/RF Systems

Tutorial on Remote Sensing Using GNSS Bistatic Radar of Opportunity

GNSS-IR Model of Sea Level Height Estimation Combining Variational Mode Decomposition

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