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Digital Processing Of Synthetic Aperture Radar Data Download

The concept of an image is only introduced after Level 1 processing, which re-arranges the Level 0 samples in azimuth and range bins to locations on earth. In order to keep Level 1 images at a reasonable size (e.g., for downloading), the Level 0 data is cut into azimuth time slices of 25 seconds (for IW), which are then processed to GRD. This is where the term frame or scene is often used. 25 seconds of azimuth time corresponds to approximately 185 km on the ground.

digital processing of synthetic aperture radar data download

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Since the range swath width in the conventional single channel spaceborne synthetic aperture radar (SAR) is restricted by the system parameters, there is a trade-off between the azimuth resolution and the swath width in order to satisfy the Nyquist sampling criterion. In this paper, we propose a novel spaceborne SAR wide-swath imaging scheme based on compressive sensing (CS) for the sparse scene. The proposed method designs a Poisson disk-like nonuniform sampling pattern in the azimuth direction, which meets the demand of wider swath by restricting the smallest time interval between any two azimuth samples, with the conventional sampling pattern preserved in the range direction. By a similar way to the processing procedure of spectral analysis (SPECAN) algorithm, the linear range migration correction (RMC) is realized while carrying out range compression, which can meet the demand for focusing with middle level resolution. To reduce the computation load of CS reconstruction, we propose a novel fast reconstruction algorithm based on nonuniform fast Fourier transform (NUFFT), which greatly reduces the computation complexity from O(2MN) to O(4N logN). Experiment results validate the effectiveness of the proposed methods via the point target simulation and the Radarsat-1 raw data processing in F2 mode.

Increasing requirements to modern synthetic-aperture radars leads to a complication of both the radars themselves and the tools for monitoring of the radar parameters. Reflected-signal simulator is designed to check through characteristics of such radars at various stages of the life cycle, starting with the development of components and including regular operation, using the same methods. We describe a device for converting the sounding signals of synthetic-aperture radars to simulated reflected ones. A distinctive feature of the presented device is the ability to simulate point and spatially distributed targets and an arbitrary target environment (a set of observation conditions) for test, calibration, and validation.

To create a SAR image, successive pulses of radio waves are transmitted to "illuminate" a target scene, and the echo of each pulse is received and recorded. The pulses are transmitted and the echoes received using a single beam-forming antenna, with wavelengths of a meter down to several millimeters. As the SAR device on board the aircraft or spacecraft moves, the antenna location relative to the target changes with time. Signal processing of the successive recorded radar echoes allows the combining of the recordings from these multiple antenna positions. This process forms the synthetic antenna aperture and allows the creation of higher-resolution images than would otherwise be possible with a given physical antenna.[2]

A synthetic-aperture radar is an imaging radar mounted on an instant moving platform.[8] Electromagnetic waves are transmitted sequentially, the echoes are collected and the system electronics digitizes and stores the data for subsequent processing. As transmission and reception occur at different times, they map to different small positions. The well ordered combination of the received signals builds a virtual aperture that is much longer than the physical antenna width. That is the source of the term "synthetic aperture," giving it the property of an imaging radar.[5] The range direction is perpendicular to the flight track and perpendicular to the azimuth direction, which is also known as the along-track direction because it is in line with the position of the object within the antenna's field of view.

Synthetic-aperture radar determines the 3D reflectivity from measured SAR data. It is basically a spectrum estimation, because for a specific cell of an image, the complex-value SAR measurements of the SAR image stack are a sampled version of the Fourier transform of reflectivity in elevation direction, but the Fourier transform is irregular.[14] Thus the spectral estimation techniques are used to improve the resolution and reduce speckle compared to the results of conventional Fourier transform SAR imaging techniques.[15]

FFT (Fast Fourier Transform i.e., periodogram or matched filter) is one such method, which is used in majority of the spectral estimation algorithms, and there are many fast algorithms for computing the multidimensional discrete Fourier transform. Computational Kronecker-core array algebra[16] is a popular algorithm used as new variant of FFT algorithms for the processing in multidimensional synthetic-aperture radar (SAR) systems. This algorithm uses a study of theoretical properties of input/output data indexing sets and groups of permutations.

SAMV method is a parameter-free sparse signal reconstruction based algorithm. It achieves super-resolution and is robust to highly correlated signals. The name emphasizes its basis on the asymptotically minimum variance (AMV) criterion. It is a powerful tool for the recovery of both the amplitude and frequency characteristics of multiple highly correlated sources in challenging environment (e.g., limited number of snapshots, low signal-to-noise ratio. Applications include synthetic-aperture radar imaging and various source localization.

Backprojection Algorithm has two methods: Time-domain Backprojection and Frequency-domain Backprojection. The time-domain Backprojection has more advantages over frequency-domain and thus, is more preferred. The time-domain Backprojection forms images or spectrums by matching the data acquired from the radar and as per what it expects to receive. It can be considered as an ideal matched-filter for synthetic-aperture radar. There is no need of having a different motion compensation step due to its quality of handling non-ideal motion/sampling. It can also be used for various imaging geometries.[27]

SAR polarimetry is a technique used for deriving qualitative and quantitative physical information for land, snow and ice, ocean and urban applications based on the measurement and exploration of the polarimetric properties of man-made and natural scatterers. Terrain and land use classification is one of the most important applications of polarimetric synthetic-aperture radar (PolSAR).[34]

For PolSAR image analysis, there can be cases where reflection symmetry condition does not hold. In those cases a four-component scattering model[34][38] can be used to decompose polarimetric synthetic-aperture radar (SAR) images. This approach deals with the non-reflection symmetric scattering case. It includes and extends the three-component decomposition method introduced by Freeman and Durden[36] to a fourth component by adding the helix scattering power. This helix power term generally appears in complex urban area but disappears for a natural distributed scatterer.[34]

Rather than discarding the phase data, information can be extracted from it. If two observations of the same terrain from very similar positions are available, aperture synthesis can be performed to provide the resolution performance which would be given by a radar system with dimensions equal to the separation of the two measurements. This technique is called interferometric SAR or InSAR.

If the two samples are obtained simultaneously (perhaps by placing two antennas on the same aircraft, some distance apart), then any phase difference will contain information about the angle from which the radar echo returned. Combining this with the distance information, one can determine the position in three dimensions of the image pixel. In other words, one can extract terrain altitude as well as radar reflectivity, producing a digital elevation model (DEM) with a single airplane pass. One aircraft application at the Canada Centre for Remote Sensing produced digital elevation maps with a resolution of 5 m and altitude errors also about 5 m. Interferometry was used to map many regions of the Earth's surface with unprecedented accuracy using data from the Shuttle Radar Topography Mission.

Doppler Beam Sharpening commonly refers to the method of processing unfocused real-beam phase history to achieve better resolution than could be achieved by processing the real beam without it. Because the real aperture of the radar antenna is so small (compared to the wavelength in use), the radar energy spreads over a wide area (usually many degrees wide in a direction orthogonal (at right angles) to the direction of the platform (aircraft)). Doppler-beam sharpening takes advantage of the motion of the platform in that targets ahead of the platform return a Doppler upshifted signal (slightly higher in frequency) and targets behind the platform return a Doppler downshifted signal (slightly lower in frequency).

The process can be thought of as combining the series of spatially distributed observations as if all had been made simultaneously with an antenna as long as the beamwidth and focused on that particular point. The "synthetic aperture" simulated at maximum system range by this process not only is longer than the real antenna, but, in practical applications, it is much longer than the radar aircraft, and tremendously longer than the radar spacecraft.


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