Multiprocessor DSP for real time data processing on earth orbiting scatterometers
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digital signal processing scatterometer radar↗
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Atmospheric Form Drag Coefficients Over Arctic Sea Ice Using Remotely Sensed Ice Topography Data, Spring 2009-2015
Sea ice topography significantly impacts turbulent energy/momentum exchange, e.g., atmospheric (wind) drag, over Arctic sea ice. Unfortunately, observational estimates of this contribution to atmospheric drag variability are spatially and temporally limited. Here we present new estimates of the neutral atmospheric form drag coefficient over Arctic sea ice in early spring, using high-resolution Airborne Topographic Mapper elevation data from NASA's Operation IceBridge mission. We utilize a new three-dimensional ice topography data set and combine this with an existing parameterization scheme linking surface feature height and spacing to form drag. To be consistent with previous studies investigating form drag, we compare these results with those produced using a new linear profiling topography data set. The form drag coefficient from surface feature variability shows lower values [less than 0.5-1 × 10(exp. −3)] in the Beaufort/Chukchi Seas, compared with higher values [greater than 0.5-1 ×10(exp. −3)] in the more deformed ice regimes of the Central Arctic (north of Greenland and the Canadian Archipelago), which increase with coastline proximity. The results show moderate interannual variability, including a strong increase in the form drag coefficient from 2013 to 2014/2015 north of the Canadian Archipelago. The form drag coefficient estimates are extrapolated across the Arctic with Advanced Scatterometer satellite radar backscatter data, further highlighting the regional/interannual drag coefficient variability. Finally, we combine the results with existing parameterizations of form drag from floe edges (a function of ice concentration) and skin drag to produce, to our knowledge, the first pan-Arctic estimates of the total neutral atmospheric drag coefficient (in early spring) from 2009 to 2015.
sea ice↗
Radar backscatter measurement accuracies using digital Doppler processors in spaceborne scatterometers
The normalized standard deviation, Kp, of radar backscatter measurements using digital Doppler processors in spaceborne scatterometers is derived. The Kp expression for analog Doppler filter processors, such as that used in the Seasat scatterometer is shown to be a special case of the derived Kp expression. A connection to Welch's (1967) power spectrum estimation rsults is also made. Tradeoff studies in digital filter design such as hardware complexity, computational speed, and system performance can be performed based on this Kp expression. A current application in the design of the NASA scatterometer to be flown in 1990 is discussed. This derivation should be useful for system design and analysis of other radar remote-sensing instruments.
Chi, C.-Y.↗
Radar progress in the NASA earth resources aircraft program
Describing development of scatterometer and imaging radar for earth resources aircraft
Moore, R. K.↗
Seasat-A and the commercial ocean community
The Seasat-A program has been initiated as a 'proof-of-concept' mission to evaluate the effectiveness of remotely sensing oceanology and related meteorological phenomena from a satellite platform in space utilizing sensors developed on previous space and aircraft test programs. The sensors include three active microwave sensors; a radar altimeter, a windfield scatterometer, and a synthetic aperture radar. A passive scanning multifrequency microwave radiometer, visual and infrared radiometer are also included. All weather, day-night measurements of sea surface temperature, surface wind speed/direction and sea state and directional wave spectra will be made. Two key programs are planned for data utilization with users during the mission. Foremost is a program with the commercial ocean community to test the utility of Seasat-A data and to begin the transfer of ocean remote sensing technology to the civil sector. A second program is a solicitation of investigations, led by NOAA, to involve the ocean science community in a series of scientific investigations.
Montgomery, D. R.↗
Microwave backscattering theory and active remote sensing of the ocean surface
The status is reviewed of electromagnetic scattering theory relative to the interpretation of microwave remote sensing data acquired from spaceborne platforms over the ocean surface. Particular emphasis is given to the assumptions which are either implicit or explicit in the theory. The multiple scale scattering theory developed during this investigation is extended to non-Gaussian surface statistics. It is shown that the important statistic for the case is the probability density function of the small scale heights conditioned on the large scale slopes; this dependence may explain the anisotropic scattering measurements recently obtained with the AAFE Radscat. It is noted that present surface measurements are inadequate to verify or reject the existing scattering theories. Surface measurements are recommended for qualifying sensor data from radar altimeters and scatterometers. Additional scattering investigations are suggested for imaging type radars employing synthetically generated apertures.
Brown, G. S.↗
On-orbit Calibration of the Seawinds Scatterometer Antennas
Measurements of ocean, sea-ice and terrain geophysical parameters can be remotely sensed using an active microwave sensor known as the microwave scatterometer. Satellite scatterometers are spaceborne radars that measure the absolute backscattered power from the earth's surface; and from this measurement, the normalized radar cross-section (sigma(sup 0)) of that surface is determined. Scatterometers calculate sigma(sup 0) of a measurement cell by inverting the radar equation [1]: where: R is range to the cell center, P(sub t) is transmitted power, lambda is transmitted wavelength, L is total path loss, G(sub A) is peak antenna gain, A(sub c) is cell area, and c is a pre-computed factor due to the approximation of the radar equation for extended area targets.
Zec, Josko↗
Studies of the radar cross section variations near the frontal boundary during Fasinex
The relationship between Amscat scatterometer measurements during Fasinex (the Frontal Air-Sea Interaction Experiment) and surface winds, waves, and surface stress is studied. Fasinex, which took place during the winter/spring of 1985-1986, focused on an oceanic front in the subtropical convergence zone southwest of Bermuda. Particular attention is given to data collected on February 18 when the Ku-band scatterometer measured the radar cross sections along two 80-km flight paths that ran north-south, approximately perpendicular to the front boundary.
Weissman, David E.↗
The SASS scattering coefficient algorithm
This paper describes the algorithms used to convert engineering unit data obtained from the Seasat-A satellite scatterometer (SASS) to radar scattering coefficients and associated supporting parameters. A description is given of the instrument receiver and related processing used by the scatterometer to measure signal power backscattered from the earth's surface. The applicable radar equation used for determining scattering coefficient is derived. Sample results of SASS data processed through current algorithm development facility (ADF) scattering coefficient algorithms are presented which include scattering coefficient values for both water and land surfaces. Scattering coefficient signatures for these two surface types are seen to have distinctly different characteristics. Scattering coefficient measurements of the Amazon rain forest indicate the usefulness of this type of data as a stable calibration reference target.
Bracalente, E. M.↗
Effect of precipitation on choice of frequency for SEASAT scatterometer
Precipitation backscatter limits the effectiveness of a remote sensing radar in a satellite. Scatterometer operation on SEASAT is considered in one of the following frequency ranges: 12.5 GHz; 13.4-14.0 GHz; and 14.4-15.35 GHz. The effect of backscatter from precipitation in these frequency ranges is compared.
Dome, G.↗
Analysis of Skylab 2 S193 scatterometer data
SKYLAB II S193 Scatterometer data for the passes of June 5, 1973, over the Gulf of Mexico and June 6, 1973, over Pacific Hurricane AVA were analyzed. The S193 scatterometer measured the radar cross section of the ocean at 13.9 GHz (Ku-band) as a function of incidence angle. The fields-of-view of the scatterometer were known. In the absence of a large body of Ku-band ocean radar data, the results of the NRL experiments at X-band (8.9 GHz) were used for comparison. The S193 data of June 5, 1973, when a practically uniform wind field was present, show reasonable agreement with the NRL empirical and theoretical models.
Jordan, A. K.↗
Radar activities of the DFVLR Institute for Radio Frequency Technology
Aerospace research and the respective applications microwave tasks with respect to remote sensing, position finding and communication are discussed. The radar activities are directed at point targets, area targets and volume targets; they center around signature research for earth and ocean remote sensing, target recognition, reconnaissance and camouflage and imaging and area observation radar techniques (SAR and SLAR). The radar activities cover a frequency range from 1 GHz up to 94 GHz. The radar program is oriented to four possible application levels: ground, air, shuttle orbits and satellite orbits. Ground based studies and measurements, airborne scatterometers and imaging radars, a space shuttle radar, the MRSE, and follow on experiments are considered.
Keydel, W.↗
ERS-1 scatterometer calibration and validation activities at ECMWF. B: From radar backscatter characteristics to wind vector solutions
Calibration and validation activities for the ERS-1 scatterometer were carried out at ECMWF (European Center for Medium range Weather Forecast) complementary to the 'Haltenbanken' field campaign off the coast of Norway. At a Numerical Weather Prediction (NWP) center a wealth of verifying data is available both in time and space. This data is used to redefine the wind retrieval procedure given the instrumental characteristics. It was found that a maximum likelihood estimation procedure to obtain the coefficients of a reformulated sigma deg to wind relationship should use radar measurements in logarithmic rather than physical space, and use winds as the wind components rather than wind speed and direction. Doing this, a much more accurate transfer function than the one currently operated by ESA was derived. Sigma deg measurement space shows no signature of a separation in an upwind solution cone and a downwind solution cone. As such signature was anticipated in ESA's wind direction ambiguity removal algorithm, reconsideration of the procedure is necessary. Despite the fact that revisions have to be made in the process of wind retrieval; a grid potential is shown for scatterometry in meteorology and climatology.
Stoffelen, AD↗
Advanced Techniques for Improving Wind Direction Ambiguity Removal in Scatterometry
Ocean surface winds, which drive the ocean currents and momentum flux exchanges, are critical for atmospheric and oceanographic studies. Ocean surface winds also generate small capillary waves which affect the normalized radar cross section of the ocean surface. A scatterometer is a microwave radar which measures these cross section values. This talk describes related new techniques.
Scatterometry↗
Multiprocessor DSP for real-time data processing on Earth orbiting scatterometers
The implementation of a Multi DSP radar signal processor for a Ku-Band Earth orbiting scatterometer is discussed. A testbed has been assembled using a combination of commercial DSP hardware and spaceflight components to evaluate the proposed multiprocessing approaches. Test results of real-time radar echo processing are presented, as well as proposed designs for future investigation.
digital signal processing scatterometer radar↗
Seasat mission overview
The microwave oceanographic satellite Seasat is described, and the main characteristics of its five sensors, including a radar altimeter, the Seasat-A scatterometer system, a synthetic aperture radar, a visual and infrared radiometer, and a scanning multichannel microwave radiometer, are discussed. Experimental programs undertaken by the satellite are briefly summarized.
Born, G. H.↗