SAR Image Processing Using Artificial Intelligence Planning
In recent times, improvements in imaging technology have made available an incredible array of information in image format.
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Sea ice motion measurements from Seasat SAR images
Data from the Seasat synthetic aperture radar (SAR) experiment are analyzed in order to determine the accuracy of this information for mapping the distribution of sea ice and its motion. Data from observations of sea ice in the Beaufort Sea from seven sequential orbits of the satellite were selected to study the capabilities and limitations of spaceborne radar application to sea-ice mapping. Results show that there is no difficulty in identifying homologue ice features on sequential radar images and the accuracy is entirely controlled by the accuracy of the orbit data and the geometric calibration of the sensor. Conventional radargrammetric methods are found to serve well for satellite radar ice mapping, while ground control points can be used to calibrate the ice location and motion measurements in the cases where orbit data and sensor calibration are lacking. The ice motion was determined to be approximately 6.4 + or - 0.5 km/day. In addition, the accuracy of pixel location was found over land areas. The use of one control point in 10,000 sq km produced an accuracy of about + or 150 m, while with a higher density of control points (7 in 1000 sq km) the location accuracy improves to the image resolution of + or - 25 m. This is found to be applicable for both optical and digital data.
Leberl, F.↗
Determination of noise equivalent sigma(0) using highly correlated repeat-pass SAR images
Noise equivalent sigma(sup 0) is a fundamental parameter in any synthetic aperture radar (SAR) measurement. Knowledge of the noise equivalent sigma(sup 0) allows the radar application scientist to band the error contributions due to noise present in his/her data. In this paper, a novel technique for determining noise equivalent sigma(sup 0) is presented. It has been observed that a pair of images obtained by a SAR over the same area in a nearly repeating orbit can demonstrate a high degree of correlation, depending on the baseline. If noise independence and signal power invariance are assumed, an estimate for the noise equivalent sigma(sup 0) for each image can be determined without any known ground targets. We examine the application of this technique to several images of different backscatter obtained by ERS-1.
Sun, James↗
Real-time SAR image processing onboard a Venus orbiting spacecraft
The potential use of real-time SAR processing to produce 200-meter resolution imagery onboard a 1983 Venus Orbiter Imaging Radar (VOIR) spacecraft is discussed. The current NASA SAR processor development program and its relationship to the VOIR application are described. VOIR SAR processing requirements are defined in terms of a nominal baseline design evolving from a 1977 VOIR mission study by JPL. A candidate onboard SAR processor architecture compatible with the VOIR requirements is described. Detailed implementation characteristics, based on currently available integrated circuits, are estimated in terms of chip count, weight, and power.
Arens, W. E.↗
The Effects of Faraday Rotation on Backscatter Signatures in SAR Image Data
The effect of Faraday rotation on spaceborne polarimetric SAR measurements is addressed. Single-polarized, dual-polarized and quad-polarized backscatter measurements subject to Faraday rotation are modeled.
Faraday↗
Future SAR Imaging Systems: Goals, Plans, Challenges and Opportunities
Synthetic Aperture Radar (SAR) Earth observation data are becoming increasingly ubiquitous as new spaceborne systems become operational and their data are made available to scientists and applications users. The characteristic of active sensors like SAR to be able to observe Earth independent of weather or solar illumination, coupled with regular data acquisition, fosters reliability and encourages the investment in algorithm and product development toward a beneficial result. As SAR systems typically contain proprietary or nationally important technologies, civilian SAR systems are typically developed with a national focus, or in the case of the European Union, with the Union’s focus. As a result, when viewed from a global perspective, SAR programs can be generally viewed as independent developments, each with their own requirements, schedules, development approaches, and data policies. At the same time, these systems can be expensive, and particularly in an era of increasingly open data policies, coordination of programs could reduce redundancy in observations, increase sampling density and measurement diversity, and improve dependability of data streams in the long term. Since 2018, agency representatives from NASA, ESA, DLR, JAXA, ISRO, ASI, and CONAE have been evaluating the possibilities for programmatic and technical coordination of future SAR systems, data sharing, and scientific exploitation. In this paper, we describe the work in discovering trends and possibilities associated with flight systems, by evaluating current and future plans for SAR systems around the world, and identifying opportunities for coordination.
Zink, Manfred↗
Rapid-Repeat SAR Imaging of the Ocean Surface: Can We Get Daily Observation
Imaging of the ocean surface with a synthetic aperture radar (SAR) provides unprecedented detailed views of the ocean's short wave field as it responds to interactions with the atmosphere, longer waves and currents.
SAR Ocean Surface Imaging↗
Real-time SAR image processing onboard a Venus orbiting spacecraft
The potential use of real-time synthetic aperture radar (SAR) processing to produce 200 meter resolution imagery onboard a 1983 Venus orbiter imaging radar spacecraft is described. The VOIR SAR processing requirements are defined in terms of a nominal baseline design evolving from a 1977 VOIR mission study. A candidate onboard SAR processor architecture compatible with the VOIR requirements is next detailed. Finally, implementation characteristics, based upon currently available integrated circuits, are estimated in terms of chip count, power, and weight.
Arens, W. E.↗
Acousto-optic techniques for real SAR imaging
Recent advancements in the development of the Real Time Acousto-optic SAR Processor are presented. In particular, the technique for introducing the azimuth reference function into the processor via an acousto-optic Bragg cell is discussed. This approach permits the reference function to be stored in electronic memory, thus giving the processor the flexibility needed to adapt rapidly to changes in the radar/target geometry. The architecture is described and results are presented which show the applicability of the technique to both spot-light and strip-map SAR.
Haney, M.↗
Four channel simultaneous X-L band imaging SAR radar
Design considerations, construction, and testing of a four-channel microwave radar imaging system are described. Various components of the system are described in some detail including the receiver, transmitter, recorders, and the general timing circuitry. Results from flight tests of the system are described. The system is unique in that images from four microwave channels are provided and the data is obtained simultaneously. Energy is radiated at both 3 cm and 25 cm wavelengths; the four receiving channels are 3 cm, like and crossed polarization and 25 cm, like and crossed polarization.
Rawson, R.↗
SAR Image Processing Using Artificial Intelligence Planning
In recent times, improvements in imaging technology have made available an incredible array of information in image format.
automation↗
Separation of vegetation and rock signatures in Thematic Mapper and polarimetric SAR images
A technique for separating classes of surface roughness and vegetation in semiarid regions using polarimetric synthetic aperture radar (SAR) and Thematic Mapper data is developed. Polarimetric SAR data may be used to separate areas with less than 10 percent vegetation cover where one suite of model inversions may be applicable for derivation of surface roughness. In more vegetated regions, visible/near-infrared data provide a mechanism for determining the relative contribution of vegetation to multiple scattering in the SAR data. Thus, the synergistic use of the two data sets provides a more complete characterization of surface units and cover. This result is critical when trying to monitor dielectric constant variations related to changes in moisture content of soil and vegetation cover in arid to semiarid regions. A strategy for automating a procedure for measurement of surface roughness is proposed.
Evans, Diane L.↗
Using Artificial Intelligence Planning to Automate SAR Image Processing for Scientific Data Analysis
In recent times, improvements in imaging technology have made available an incredible array of information in image format.
image processing AI planning synthetic aperture ra↗
An improvement in SAR image interpretability provided by post-correlation signal processing
A presentation on the basis of subjective analysis of computer-generated SAR imagery depicts the improvement in interpretability obtained by post-correlation signal processing. A parametric study was conducted to determine the improvement in interpretability obtained by the application of signal weighting functions on the post-processed returns. The results suggest that a marked improvement in interpretability results from symmetrizing the exponential distribution of the fading signal. Preliminary analysis indicates that signal weighting improves the contrast ratio between the mean value of adjacent homogeneous regions in a SAR scene.
Matthews, N. D.↗
SAR image enhancement via post-correlation signal processing
Seventeen interpreters ranked sets of computer-generated radar imagery to assess the value of post-correlation processing on the interpretability of SAR (synthetic aperture radar) imagery. The post-correlation processing evaluated amounts to a nonlinear mapping of the signal exiting a digital correlator and allows full use of signal bandwidth for improving the spatial resolution or for noise reduction. The results indicate that it is reasonable to hypothesize an optimal SAR presentation format for specific applications even though this study was too limited to be specific.
Matthews, N. D.↗
Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data
An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.
Shi, Jian-Cheng↗
Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data
An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quasi-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well-managed watershed in southwest Oklahoma. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.
Shi, Jian-Cheng↗