200 research outputs found
Basics of Polar-Format algorithm for processing Synthetic Aperture Radar images.
The purpose of this report is to provide a background to Synthetic Aperture Radar (SAR) image formation using the Polar Format (PFA) processing algorithm. This is meant to be an aid to those tasked to implement real-time image formation using the Polar Format processing algorithm
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Reflectors for SAR performance testing.
Synthetic Aperture Radar (SAR) performance testing and estimation is facilitated by observing the system response to known target scene elements. Trihedral corner reflectors and other canonical targets play an important role because their Radar Cross Section (RCS) can be calculated analytically. However, reflector orientation and the proximity of the ground and mounting structures can significantly impact the accuracy and precision with which measurements can be made. These issues are examined in this report
Une comparaison de structures: "Une Mort héroïque" de Baudelaire et "Après la Déluge" de Rimbaud
Window taper functions for subaperture processing
It is well known that the spectrum of a signal can be calculated with a Discrete Fourier Transform (DFT), where best resolution is achieved by processing the entire data set. However, in some situations it is advantageous to use a staged approach, where data is first processed within subapertures, and the results are then combined and further processed to a final result. An artifact of this approach is the creation of grating lobes in the final response. The nature of the grating lobes, including their amplitude and spacing, is an artifact of window taper functions, subaperture offsets, and subaperture processing parameters. We assess these factors and exemplify their effects
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Patch diameter limits for tiered subaperture SAR image formation algorithms
Synthetic Aperture Radar image formation algorithms typically use transform techniques that often requires trading between image resolution, algorithm efficiency, and focussed image scene size limits. This is due to assumptions for the data such as simplified (often straight-line) flight paths, simplified imaging geometry, and simplified models for phase functions. Many errors in such assumptions are typically untreatable due to their dependence on both data domain positions and image domain positions. The result is that large scenes often require inefficient multiple image formation iterations, followed by a mosaicking operation of the focussed image patches. One class of image formation algorithms that performs favorably divides the spatial and frequency apertures into subapertures, and perhaps those subapertures into sub-subapertures, and so on, in a tiered subaperture fashion. This allows a gradual shift from data domain into image domain that allows correcting many types of errors that limit other image formation algorithms, even in a dynamic motion environment, thereby allowing larger focussed image patches without mosaicking. This paper presents and compares focussed patch diameter limits for tiered subaperture (TSA) image formation algorithms, for various numbers of tiers of subapertures. Examples are given that show orders-of-magnitude improvement in non-mosaicked focussed image patch size over traditional polar format processing, and that patch size limits increase with the number of tiers of subapertures, although with diminishing returns
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Automatic compensation of antenna beam roll-off in SAR images.
The effects of a non-uniform antenna beam are sometimes visible in Synthetic Aperture Radar (SAR) images. This might be due to near-range operation, wide scenes, or inadequate antenna pointing accuracy. The effects can be mitigated in the SAR image by fitting very a simple model to the illumination profile and compensating the pixel brightness accordingly, in an automated fashion. This is accomplished without a detailed antenna pattern calibration, and allows for drift in the antenna beam alignments
Performance limits for maritime Inverse Synthetic Aperture Radar (ISAR)
The performance of an Inverse Synthetic Aperture Radar (ISAR) system depends on a variety of factors, many which are interdependent in some manner. In this report we specifically examine ISAR as applied to maritime targets (e.g. ships). It is often difficult toget your arms around' the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall ISAR system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing theseek time'
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Collection and processing data for high quality CCD images.
Coherent Change Detection (CCD) with Synthetic Aperture Radar (SAR) images is a technique whereby very subtle temporal changes can be discerned in a target scene. However, optimal performance requires carefully matching data collection geometries and adjusting the processing to compensate for imprecision in the collection geometries. Tolerances in the precision of the data collection are discussed, and anecdotal advice is presented for optimum CCD performance. Processing considerations are also discussed
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