Space-based Radio Occultation (RO) measurements using a GPS receiver on a low Earth orbiter (LEO) provide accurate atmospheric refractivity profiles. EQUatorial Atmospheric Research Satellite (EQUARS) is a planned satellite mission carrying a GPS receiver for RO measurements, whose main focus is to study the vertical coupling process in the equatorial atmosphere and ionosphere through upward propagating atmospheric waves. This paper presents a model simulation to determine the best practical orbital parameters of a LEO satellite for GPS occultation, which provides dense occultation coverage from 20• S to 20• N and sparser coverage extending to 30• S and 30• N. Constellations of 29 GPS satellites are computed every 10 sec using the six Keplerian parameters based on real almanac data, while various orbits of LEO satellite are computed by varying orbital parameters, especially orbital altitude and inclination. Then, the occultation events are simulated under the assumption that the ray path between the occulting GPS and LEO satellites is a straight line. The simulation analysis shows that altitude and inclination angle of orbit are considered as principal parameters among the Keplerian parameters to accomplish the RO measurements in the equatorial region. Taking into account the long-lived mission, an avoidance of ionospheric F-layer influences, and practical antenna field of view, the best practical orbit for RO measurement in the equatorial region has an altitude of 750 km and an inclination of 20• . LEO on this orbit is expected to provide 530 RO events per day. The analysis also shows that three LEOs in that orbit with 120• separation can provide atmospheric profiles at least once every 6 h within 1000 km from an arbitrary station in the equator.

Tropospheric delay computation is necessary to improve GPS measurements accuracy. Precise determination of these propagation delays requires knowledge of the full refraction profile at signal path. In the present research, precise troposphere slant delay model (PTD) is derived based on ten stations of radiosonde data well-distributed over and around Egypt. To derive the PTD, the troposphere is divided into regular small layers. Ray tracing technique of actual signal path traveled in the troposphere is used to estimate tropospheric slant delay. Real GPS data of six stations in 8-day period were used for the assessment of zenith part of PTD model against the available international models. These international models include Saastamoinen, Hopfield, and the local Egyptian dry model proposed by Mousa & El-Fiky. The data were processed using Bernese software version 5.0. The closure error results indicate that the PTD model is the best model in all session, but when the available radiosonde stations are less, the accuracy of PTD model is near to classic models. As radiosonde data for all ten stations are not available every session, it is recommended to use one of the regularization techniques for database to overcome missing data and derive consistent tropospheric delay information.

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This paper presents an efficient change detection approach for Synthetic Aperture Radar (SAR) images. The basic idea of this approach is to use the log ratio of the two images for change detection after being registered with Scale-Invariant Feature Transform (SIFT). These two images are a reference image and another image for the same area acquired at a different time. The log ratio variations include changes in certain areas corresponding to the natural changes in the test image. Usually, SAR images contain some sort of noise. So, there is a need for a denoising process prior to estimating the log ratio to enhance the change detection results. A segmentation process is performed on the test image based on the log ratio values. Large values in the log ratio image correspond to detected changes in the test image. Simulation results on SAR images for a region of Jeddah demonstrate the success of the proposed approach.