Retrieval of Ocean Surface Wind Speed and Wind Direction Using Reflected GPS Signals
01 Mar 2004-Journal of Atmospheric and Oceanic Technology (American Meteorological Society)-Vol. 21, Iss: 3, pp 515-526
TL;DR: In this article, reflected GPS measurements were collected using aircraft with a delay mapping GPS receiver for determining ocean surface wind speed and direction during flights to Hurricanes Michael and Keith in October 2000.
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 ms 21 shows an overall agreement of better than 2 m s 21 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 308 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.
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TL;DR: A new remotesensing technique to use reflected GNSS signals for remote-sensing applications is described, some of the interesting results that have been already obtained are discussed, and an overview of current and planned spacecraft missions is given.
Abstract: -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.
395 citations
Cites background or methods from "Retrieval of Ocean Surface Wind Spe..."
...There is a general agreement that GNSS-R is sensitive to anisotropies and wind direction with 180° ambiguity [16], [18], [168], [177], [180]....
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...It was suggested and tested in airborne campaigns in [16], [18]....
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...This includes the retrieval of wind speed and later wind vector above rough seas using reflected signals from multiple GPS satellites [15]–[18]....
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TL;DR: In this paper, the authors presented results for ocean surface wind speed retrieval from reflected GPS signals measured by the Low Earth-Orbiting UK TechDemoSat-1 satellite (TDS-1).
Abstract: First results are presented for ocean surface wind speed retrieval from reflected GPS signals measured by the Low-Earth-Orbiting UK TechDemoSat-1 satellite (TDS-1). Launched in July 2014, TDS-1 provides the first new spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) data since the pioneering UK-Disaster Monitoring Mission experiment in 2003. Examples of onboard-processed delay Doppler Maps reveal excellent data quality for winds up to 27.9 m/s. Collocated ASCAT scatterometer winds are used to develop and evaluate a wind speed algorithm based on Signal-to-Noise ratio (SNR) and the Bistatic Radar Equation. For SNR greater than 3 dB, wind speed is retrieved without bias and a precision around 2.2 m/s between 3–18 m/s even withoutcalibration. Exploiting lower SNR signals however requires good knowledge of the antenna beam, platform attitude and instrument gain setting. This study demonstrates the capabilities of low-cost, low-mass, low-power GNSS-R receivers ahead of their launch on the NASA CYGNSS constellation in 2016.
251 citations
TL;DR: In this paper, the authors present the current status and new developments of remote sensing using Global Navigation Satellite System (GNSS) signals as well as its future directions and applications, including monitoring sea ice, dangerous sea states, ocean eddy and storm surges.
191 citations
Cites background from "Retrieval of Ocean Surface Wind Spe..."
...…speed and (occasionally) direction were determined from GNSS reflected signals under well developed sea conditions as well as soil moisture, snow and ice thickness (Komjathy et al., 2000; Rius et al., 2002; Germain et al., 2004; Masters, 2004; Komjathy et al., 2004; Belmonte-Rivas et al., 2010)....
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...The wave height, wind speed and (occasionally) direction were determined from GNSS reflected signals under well developed sea conditions as well as soil moisture, snow and ice thickness (Komjathy et al., 2000; Rius et al., 2002; Germain et al., 2004; Masters, 2004; Komjathy et al., 2004; Belmonte-Rivas et al., 2010)....
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TL;DR: A retrieval algorithm is presented for the Level 2 ocean surface wind speed data product of the Cyclone Global Navigation Satellite System (CYGNSS) mission based on the approach described by Clarizia et al .
Abstract: A retrieval algorithm is presented for the Level 2 ocean surface wind speed data product of the Cyclone Global Navigation Satellite System (CYGNSS) mission. The algorithm is based on the approach described by Clarizia et al ., 2014. The approach is applied to the specific orbital measurement geometry, antenna, and receiver hardware characteristics of the CYGNSS mission. Several additional processing steps have also been added to improve the performance. A best weighted estimator is used to optimally combine two different partially correlated estimates of the winds by taking their weighted average. The optimal weighting dynamically adjusts for variations in the signal-to-noise ratio of the observations that result from changes in the measurement geometry. Variations in the incidence angle of the measurements are accounted for by the use of a 2-D geophysical model function that depends on both wind speed and incidence angle. Variations in the propagation time and signal Doppler shift at different measurement geometries affect the instantaneous spatial resolution of the measurements, and these effects are compensated by a variable temporal integration of the data. In addition to a detailed description of the algorithm itself, the root-mean-square wind speed retrieval error is characterized as a function of the measurement geometry and the wind speed using a detailed mission end-to-end simulator.
185 citations
TL;DR: In this article, a prototype GPS bistatic radar participated in airborne measurements during the Soil Moisture Experiment 2002 (SMEX02) and was mounted on the NCAR C-130 aircraft to make co-located measurements with other instruments.
174 citations
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"Retrieval of Ocean Surface Wind Spe..." refers methods in this paper
...In the algorithm, residuals are minimized using a Nelder–Mead simplex (direct search) method to adjust the state (see, e.g., Press et al. 1986)....
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...Using these positions and the GPS reference ellipsoid (also known as WGS-84, Parkinson et al. 1996a,b), an estimate of the specular reflecting point coordinates on the earth’s surface is computed....
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Journal Article•
TL;DR: Differential GPS and Integrity Monitoring differential GPS Pseudolites Wide Area Differential GPS Wide Area Augmentation System Receiver Autonomous Integrity Monitoring Integrated Navigation Systems Integration of GPS and Loran-C GPS and Inertial Integration Receiver Aut autonomous Integrity Monitoring Availability for GPS Augmented with Barometric Altimeter Aiding and Clock Coasting
Abstract: Differential GPS and Integrity Monitoring Differential GPS Pseudolites Wide Area Differential GPS Wide Area Augmentation System Receiver Autonomous Integrity Monitoring Integrated Navigation Systems Integration of GPS and Loran-C GPS and Inertial Integration Receiver Autonomous Integrity Monitoring Availability for GPS Augmented with Barometric Altimeter Aiding and Clock Coasting GPS and Global Navigation Satellite System (GLONASS) GPS Navigation Applications Land Vehicle Navigation and Tracking Marine Applications Applications of the GPS to Air Traffic Control GPS Applications in General Aviation Aircraft Automatic Approach and Landing Using GPS Precision Landing of Aircraft Using Integrity Beacons Spacecraft Attitude Control Using GPS Carrier Phase Special Applications GPS for Precise Time and Time Interval Measurement Surveying with the Global Position System Attitude Determination Geodesy Orbit Determination Test Range Instrumentation.
2,409 citations
Book•
01 Jan 1996
TL;DR: Differential GPS and Integrity Monitoring Differential GPS Pseudolites Wide Area differential GPS Wide Area Augmentation System Receiver Autonomous Integrity Monitoring Integrated Navigation Systems Integration of GPS and Loran-C GPS and Inertial Integration Receiver Autonomic Integrity Monitoring Availability for GPS Augmented with Barometric Altimeter Aiding and Clock Coasting GPS and Global Navigation Satellite System (GLONASS) GPS Navigation Applications Land Vehicle Navigation and Tracking Marine Applications Applications of the GPS to Air Traffic Control GPS Applications in General Aviation Aircraft Automatic Approach and Landing of Aircraft Using Integrity Beacons Spacecraft Attitude
Abstract: Differential GPS and Integrity Monitoring Differential GPS Pseudolites Wide Area Differential GPS Wide Area Augmentation System Receiver Autonomous Integrity Monitoring Integrated Navigation Systems Integration of GPS and Loran-C GPS and Inertial Integration Receiver Autonomous Integrity Monitoring Availability for GPS Augmented with Barometric Altimeter Aiding and Clock Coasting GPS and Global Navigation Satellite System (GLONASS) GPS Navigation Applications Land Vehicle Navigation and Tracking Marine Applications Applications of the GPS to Air Traffic Control GPS Applications in General Aviation Aircraft Automatic Approach and Landing Using GPS Precision Landing of Aircraft Using Integrity Beacons Spacecraft Attitude Control Using GPS Carrier Phase Special Applications GPS for Precise Time and Time Interval Measurement Surveying with the Global Position System Attitude Determination Geodesy Orbit Determination Test Range Instrumentation.
2,275 citations