Synthetic Aperture Radar (SAR) is capable of producing high-resolution terrain images from data collected by a relatively small airborne or spaceborne antenna. This data collection is done in cross-range or slow-time along flight trajectory and range or fast-time along direction of electromagnetic wave propagation. The slow-time imaging is what distinguishes SAR from its predecessor imaging radars. The high resolution pulse compression based fast-time imaging in range introduces some visual artifacts into SAR imagery due to range skew and phase information anomaly due to residual video phase (RVP). In this paper, we introduce the concept of SAR 2D aperture synthesis that extends the slow-time imaging concept to range and relies on a single frequency instead of chirp. Moreover, our 2D aperture synthesis implementation does not need computationally expensive Stolt interpolation.
High-resolution false-color Cassini synthetic aperture radar mosaic of Titan's north polar region, showing hydrocarbon seas, lakes and tributary networks. Blue coloring indicates low radar reflectivity areas, caused by bodies of liquid ethane, methane and dissolved nitrogen.[1] About half of Kraken Mare, the large body at lower left, is outside the image. Ligeia Mare is the large body at lower right. Punga Mare is just left of center. Jingpo Lacus is just above Kraken Mare, and Bolsena Lacus is directly above it.
Synthetic Aperture Radar Christopher F. Barnes
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Activities applying AI to remote satellite data range from detecting flood and ice from synthetic-aperture radar (SAR) images (e.g., Wang et al. 2017) to estimating tropical cyclone intensity from satellite microwave imagery (Wimmers et al. 2019) to a variety of uses of AI techniques in satellite data calibration, bias correction, and remote sensing of atmospheric and surface parameters (Reichstein et al. 2019). Preparing the data (e.g., labeling) for AI exploitation is a notable challenge in some applications. This critical but often overlooked step has attracted some recent attention (e.g., Bonfanti et al. 2018; Lee et al. 2019; Prabhat et al. 2020) and should be an emphasis of future efforts by prediction centers. This will not only provide more readily available datasets for AI exploitation, it should also in principle allow more creative ways to exploit satellite data.
Cassini observations show that Saturn's moon Titan is slightly oblate. A fourth-order spherical harmonic expansion yields north polar, south polar, and mean equatorial radii of 2574.32 +/- 0.05 kilometers (km), 2574.36 +/- 0.03 km, and 2574.91 +/- 0.11 km, respectively; its mean radius is 2574.73 +/- 0.09 km. Titan's shape approximates a hydrostatic, synchronously rotating triaxial ellipsoid but is best fit by such a body orbiting closer to Saturn than Titan presently does. Titan's lack of high relief implies that most--but not all--of the surface features observed with the Cassini imaging subsystem and synthetic aperture radar are uncorrelated with topography and elevation. Titan's depressed polar radii suggest that a constant geopotential hydrocarbon table could explain the confinement of the hydrocarbon lakes to high latitudes.
This recent image of Titan reveals more complex patterns of bright and dark regions on the surface, including a small, dark, circular feature, completely surrounded by brighter material. During the two most recent flybys of Titan, on March 31 and April 16, 2005, Cassini captured a number of images of the hemisphere of Titan that faces Saturn. The image at the left is taken from a mosaic of images obtained in March 2005 (see PIA06222) and shows the location of the more recently acquired image at the right. The new image shows intriguing details in the bright and dark patterns near an 80-kilometer-wide (50-mile) crater seen first by Cassini's synthetic aperture radar experiment during a Titan flyby in February 2005 (see PIA07368) and subsequently seen by the imaging science subsystem cameras as a dark spot (center of the image at the left). Interestingly, a smaller, roughly 20-kilometer-wide (12-mile), dark and circular feature can be seen within an irregularly-shaped, brighter ring, and is similar to the larger dark spot associated with the radar crater. However, the imaging cameras see only brightness variations, and without topographic information, the identity of this feature as an impact crater cannot be conclusively determined from this image. The visual infrared mapping spectrometer, which is sensitive to longer wavelengths where Titan's atmospheric haze is less obscuring -- observed this area simultaneously with the imaging cameras, so those data, and perhaps future observations by Cassini's radar, may help to answer the question of this feature's origin. The new image at the right consists of five images that have been added together and enhanced to bring out surface detail and to reduce noise, although some camera artifacts remain. These images were taken with the Cassini spacecraft narrow-angle camera using a filter sensitive to wavelengths of infrared light centered at 938 nanometers -- considered to be the imaging science subsystem's best spectral filter
The northern and southern hemispheres of Titan are seen in these polar stereographic maps, assembled in 2015 using the best-available images of the giant Saturnian moon from NASA's Cassini mission. The images were taken by Cassini's imaging cameras using a spectral filter centered at 938 nanometers, allowing researchers to examine variations in albedo (or inherent brightness) across the surface of Titan. These maps utilize imaging data collected through Cassini's flyby on April 7, 2014, known as "T100." Titan's north pole was not well illuminated early in Cassini's mission, because it was winter in the northern hemisphere when the spacecraft arrived at Saturn. Cassini has been better able to observe northern latitudes in more recent years due to seasonal changes in solar illumination. Compared to the previous version of Cassini's north polar map (see PIA11146), this map provides much more detail and fills in a large area of missing data. The imaging data in these maps complement Cassini synthetic aperture radar (SAR) mapping of Titan's north pole (see PIA17655). The uniform gray area in the northern hemisphere indicates a gap in the imaging coverage of Titan's surface, to date. The missing data will be imaged by Cassini during flybys on December 15, 2016 and March 5, 2017. Lakes are also seen in the southern hemisphere map, but they are much less common than in the north polar region. Only a lakes have been confirmed in the south. The dark, footprint-shaped feature at 180 degrees west is Ontario Lacus; a smaller lake named Crveno Lacus can be seen as a very dark spot just above Ontario. The dark-albedo area seen at the top of the southern hemisphere map (at 0 degrees west) is an area called Mezzoramia. Each map is centered on one of the poles, and surface coverage extends southward to 60 degrees latitude. Grid lines indicate latitude in 10-degree increments and longitude in 30-degree increments. The scale in the full-size versions of these maps is 4,600 feet (1
This synthetic-aperture radar image was obtained by NASA's Cassini spacecraft during its T-120 pass over Titan's southern latitudes on June 7, 2016. The image is centered near 47 degrees south, 153 degrees west. It covers an area of 87 by 75 miles (140 by 120 kilometers) and has a resolution of about 1,300 feet (400 meters). Radar illuminates the scene from the left at a 35-degree incidence angle. The features seen here are an excellent example of "labyrinth terrain." Labyrinth terrains on Titan are thought to be higher areas that have been cut apart by rivers of methane, eroded or dissolved as they were either lifted up or left standing above as the region around them lowered. (Other examples of labyrinth terrain can be seen in PIA10219.) In this image, several obvious valley systems have developed, draining liquids from methane rainfall toward the southeast (at top). Several of these systems are near parallel (running from upper left to lower right), suggesting that either the geological structure of the surface or the local topographic gradient (the general slope across the area) may be influencing their direction. Also presented here is an annotated version of the image, along with an aerial photograph of a region in southern Java known as Gunung Kidul that resembles this Titan labyrinth. This region is limestone that has been dissolved and eroded by water, creating a system of canyons called polygonal karst. Like on Titan, the canyons show a trend from upper left to lower right, in this case controlled by faults or joints. (Java photo from Haryono and Day, Journal of Cave and Karst Studies 66 (2004) 62-69, courtesy of Eko Haryono.)
Titan`s atmosphere is essentially transparent to Radar, making it an ideal technique to study Titan`s surface. Cassini`s Titan Radar Mapper operates as a passive radiometer, scatterometer, altimeter, and synthetic aperture radar (SAR). Here we review data from four fly-bys in the first year of Cassini`s tour (Ta: October 2004, T3: February 2005, T7: September 2005, and T8: October 2005.) Early SAR images from Ta and T3 (showing 2ff7e9595c
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