The wavelength affects the azimuth resolution but it also has important implications for penetration, see Figure 8. In general, radar penetration increases with wavelength. The look angle affects layover and shadow as described above but can also have an effect on pixel brightness because it changes how the radar beam interacts with the object.
The polarization on transmit and on receive also affect the pixel brightness as described in the following section. Implementing all of these improvements, however, did require making difficult choices. The satellite also doubled in size, increasing from 48 kg to kg. Yet despite these choices, we are thrilled with the outcome— a world-class SAR satellite that delivers what our customers need and expect.
Surface Parameters The surface parameters that affect pixel brightness are the surface roughness of the material, with respect to the system wavelength and the scattering material the dielectric constant of the object. If the surface roughness of the material is smooth with respect to the system wavelength, the radar beam is reflected Figure 9 according to the law of reflection. This is called specular reflection. If the surface is rough with respect to the system wavelength, the radar beam is scattered in all directions.
This is called diffuse scattering. Varying surface roughness results in varying amounts of diffuse scattering and varying pixel brightness. The dielectric constant of the scattering material is a physical property of a material that determines how reflective that material is to electromagnetic waves. Metallic objects and water have a higher dielectric constant and are more reflective, however since they are smooth with respect to the system wavelength, and usually flat, the radar beam is specularly reflected, away from the sensor.
Additionally, certain surface features will cause a specular reflection back toward the sensor, by bouncing off multiple surfaces. A Double-bounce reflection is called a dihedral return and a Triple-bounce return is called a trihedral return. These are caused by smooth surfaces oriented at 90 degree angles to each other as seen in figure Speckle SAR is a coherent imaging method because the radio waves in a radar beam are aligned in space and time.
Speckle occurs because there are often many individual scatters in a given pixel, which leads to positive salt and negative pepper interference across pixels with an otherwise constant backscatter return. This post has described how SAR images are produced. By using clever signal processing, SAR creates radar images of higher resolution than would otherwise be possible. Jason Brown February 10, Figure 1. SAR complements photographic and other optical imaging capabilities because it is not limited by the time of day or atmospheric conditions and the unique responses of terrain and cultural targets to radar frequencies.
SAR technology provides terrain structural information to geologists for mineral exploration, oil spill boundaries on water to environmentalists, sea state and ice hazard maps to navigators, and reconnaissance and targeting information to military and intelligence operations. There are many other applications for this technology. Some of these, particularly civilian, have not yet been adequately explored because lower cost electronics are just beginning to make SAR technology economical for smaller scale uses.
A detailed description of the theory of operation of SAR is complex and beyond the scope of this site. Doerry and Fred M. Dickey is intended to give the reader an intuitive feel for how SAR works. SAR radar is partnered by what is termed Inverse SAR abbreviated to ISAR technology which in the broadest terms, utilizes the movement of the target rather than the emitter to create the synthetic aperture. ISAR radars have a significant role aboard maritime patrol aircraft to provide them with radar image of sufficient quality to allow it to be used for target recognition purposes.
The slant-range distortion occurs because the radar is measuring the distance to features in slant-range rather than the true horizontal distance along the ground.
This results in a varying image scale, moving from near to far range. Figure 4: Foreshortening. High resolution SAR urban monitoring,; ice and snow, little penetration into vegetation cover; fast coherence decay in vegetated areas. SAR Workhorse global mapping; change detection; monitoring of areas with low to moderate penetration; higher coherence ; ice, ocean maritime navigation.
Experimental SAR. Start to finish processing includes algorithms for calibration, speckle filtering, coregistration, orthorectification, mosaicking, and data conversion. Specializes in handling of acquisition metadata, formatting of preprocessed data for further analysis, and options for exporting data to Data Cube.
Interferometric processing from single look complex SLC to complex interferogram and coherence map. Includes geocoding capability, but does not include phase unwrapping. Used for phase unwrapping an interferometric process.
Interferometric processing packaged as Python modules. Interferometric processing from raw or SLC to complex interferogram and coherence map. Includes geocoding, phase unwrapping, filtering, and more. A GUI used to terrain-correct, geocode, and apply polarimetric decompositions to multi-polarimetric synthetic aperture radar PolSAR data. Python Radar Tools PyRat. Includes various filters, geometrical transformations and capabilities for both interferometric and polarimetric processing.
A GUI for high level polarimetric processing. Includes a fully polarimetric coherent SAR scattering and imaging simulator for forest and ground surfaces.
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