The most recent and advanced synthetic aperture sensors are able to work in different operating modes and are currently being installed in an increasing variety of platforms. In order to be ready to process data generated not only by these new sensors but by the incoming ones, it is important to identify the common processing blocks. For instance, different chirp scaling algorithm implementations have been analyzed to derive an approach of the same algorithm being able to process raw data in StripMap, ScanSAR and SpotLight operating modes. Next to the Radar imaging techniques, the processing software has been developed to be able to dynamically adapt its performance to the memory and CPU resources. Maximum portability has also been one of the major tasks and the same code runs under IBM and SUN UNIX, Linux and Windows 32 bits platforms. Finally, Extended Markup Language (XML) standard has been adopted for parameter, setup and report files to improve the user experience. The processing kernel and the specific modules for each operating
mode and platform have been validated using raw data from ERS-1, RADARSAT and DLR while to validate SpotLight mode, simulated data has been used for both air- and space borne platforms.
This paper presents two different approaches to detect and correct phase errors appearing in interferometric airborne SAR sensors due to the lack of precision in the navigation system. The first one is intended for interferometric pairs with high coherence, and the second one for low coherent ones. Both techniques are based on a multisquint processing approach, i.e., by processing the same image pairs with different squint angles we can combine the information of different interferograms to obtain the desired phase correction. Airborne single- and repeat-pass interferometric data from the Deutsches Zentrum fur Luft- und Raumfahrt (DLR) Experimental airborne SAR is used to validate the method.
This paper compares two different approaches for designing airborne SAR systems. The first one is the most common where conventional processing is employed, and therefore wide antenna beams are to be used in order to avoid ambiguities in the final image due to attitude variations. A second approach is proposed to lower the requirements such system imposes based on subaperture processing. The idea is to follow the azimuth variations of the Doppler centroid, without increasing the hardware requirements of the system. As it is shown in this paper, this processing procedure must be complemented with precise radiometric corrections, because the platform may experience small attitude variations, which could increase/decrease the target observation time, inducing a significant azimuth modulation in the final image. This leads to the definition of a new criterion concerning maximum attitude deviations for an airborne platform.
The increase in maritime traffic has caused an increment on the risk of accidents that can damage the environment. In recent times, the efficiency on oil spill detection and monitoring with spaceborne systems has been demonstrated. It is however important to remark that satellite data must be complemented with other monitoring platforms and sensors, for better temporal coverage and for an improvement on detection and analysis of the spill. RAPSODI is an European project for the development of a new anti-pollution remote sensing system that results from the integration of airborne sensors: SAR, SLAR, IR, UV and a microwave radiometer and spaceborne data. One of the main operational goals of this project was a real size experiment in completely controlled situations and environment. In this campaign, heavy fuel oil was released and treated. This experiment has also allowed monitoring the efficiency of the dispersing products used by the oil spill response community. In this context, this paper describes the development of the airborne SAR mode optimized for oil spill detection, and the planning and first results of the experimentation campaign.
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