The surveillance of ships at sea is a routine application that makes use of space-based Synthetic Aperture Radar (SAR) images. Presently, such applications continue to be improved upon, making use of various techniques to better detect ships in the SAR images. This paper will provide an overview of the recent improvements made to the SAR images that are used by such applications. Leveraging the programmability of the RADARSAT-2 sensor, MDA is in the process of developing and assessing two new ScanSAR beam modes: a 450km wide ship detection optimized beam mode in the HH polarization channel, and a 530km wide multi-purpose beam mode in the HH and HV polarization channels. It will be shown that these new beam modes are significantly better, offering nearly uniform ship detection of much smaller vessels across the full swath width, as compared to the existing RADARSAT-2 ScanSAR beam modes.
The RapidEye constellation includes five identical satellites in Low Earth Orbit (LEO). Each satellite has a 5-band
(blue, green, red, red-edge and near infrared (NIR)) multispectral imager at 6.5m GSD. A three-axes attitude control
system allows pointing the imager of each satellite at the Moon during lunations. It is therefore possible to image the
Moon from near identical viewing geometry within a span of 80 minutes with each one of the imagers. Comparing the
radiometrically corrected images obtained from each band and each satellite allows a near instantaneous relative
radiometric accuracy measurement and determination of relative gain changes between the five imagers. A more
traditional terrestrial vicarious radiometric calibration program has also been completed by MDA on RapidEye. The two
components of this program provide for spatial radiometric calibration ensuring that detector-to-detector response
remains flat, while a temporal radiometric calibration approach has accumulated images of specific dry dessert
calibration sites. These images are used to measure the constellation relative radiometric response and make on-ground
gain and offset adjustments in order to maintain the relative accuracy of the constellation within ±2.5%. A quantitative
comparison between the gain changes measured by the lunar method and the terrestrial temporal radiometric calibration
method is performed and will be presented.
This paper outlines the principles behind the software architecture design for a real-time processor for airborne SAR data. This processor is implemented on an MIMD parallel computer (the Meiko CS1) using a point-to-point message passing system. The processing algorithms are the result of research by the DRA, Malvern, and are capable of yielding focused, undistorted SAR imagery. Processing functions considered include: initial motion compensation (based on accelerometer data), autofucus with phase correction, and azimuth focusing. Real time processing rates of about 10 MBytes/s are now routinely achieved. We indicate the compromises between processor power, available local memory and communications bandwidth needed to achieve real-time operation. A recent development of the SAR processor has been the addition of a generic post-processing module to allow image interpretation algorithms to operate on the imagery as it is produced. Real-time SAR segmentation has been demonstrated using this facility; ports of other algorithms are planned.
Research at the DRA, Malvern, has resulted in a series of algorithms which are capable of yielding focused, undistorted SAR imagery. Unfortunately these can only be implemented in a fraction of a percent of real-time on a standard work-station. In parallel with the algorithm development, therefore, has been research into a real-time implementation on a parallel computer (the Meiko CS1). This paper outlines the principles behind the software architecture design to achieve the desired speed. Processing functions considered include: initial motion compensation (based on accelerometer data), autofocus with phase correction, final processing and an intensity segmentation stage. Real time processing rates of about 10 MBytes/s are now routinely achieved. We indicate the compromises between processor power, available local memory and communications bandwidth needed to achieve real-time operation. Detailed timings derived from the implementation will be presented together with a discussion of the manner in which this could be varied for different SAR configurations. In parallel with the work on producing real-time high quality imagery has gone a program of research into automated image-understanding techniques. This work is now reaching the stage where reliable algorithms for several basic operations, including segmentation and change detections, exist in a form capable of processing continuous imagery at real time or near real-time rates. Provision has been made for the inclusion of these algorithms as postprocessing stages in the real-time SAR processor.