The Scanning Sky Monitor (SSM) on ASTROSAT

The Scanning Sky Monitor is one of the experiments onboard the ASTROSAT, an Indian multiwavelength astronomy satellite mission. This experiment will detect and monitor X-ray transients in the energy band 2–10 keV. It is similar in design to the ASM on RXTE. It consists of position-sensitive proportional counters with one-dimensional mask. We describe the configuration of the experiment. We also discuss some of the results obtained using a detector which has already been fabricated and tested in our laboratory.     

An approach to knowledge-aided covariance estimation

This paper introduces a parametric covariance estimation scheme for use with space-time adaptive processing (STAP) methods operating in heterogeneous clutter environments. The approach blends both a priori knowledge and data observations within a parameterized model to capture instantaneous characteristics of the cell under test (CUT) and reduce covariance errors leading to detection performance loss. We justify this method using both measured and synthetic data. Performance potential for the specific operating conditions examined herein include: 1) averaged behavior within roughly 2 dB of the optimal filter, 2) 1 dB improvement in exceedance characteristic relative to the optimal filter, highlighting improved instantaneous capability, and 3) impervious ness to corruptive target-like signals in the secondary data (no additional signal-to-interference-plus-noise ratio (SINK) loss, compared with 10 dB or greater loss for the standard STAP implementation), with corresponding detections comparable to the optimal filter case     

Nighttime cloud properties retrieval using MODIS and artificial neural networks

In this work a methodology for inferring water cloud macro and microphysical properties from nighttime MODIS imagery is developed. This method is based on the inversion of a theoretical radiative transfer model that simulates the radiances detected in each of the sensor infrared bands. To accomplish this inversion, an operational technique based on Artificial Neural Networks (ANNs) is proposed, whose main characteristic is the ability to retrieve cloud properties much faster than conventional methods. Furthermore, a detailed study of input data is performed to avoid different sources of errors that appear in several MODIS infrared channels. Finally, results of applying the proposed method are compared with in-situ measurements carried out during the DYCOMS-II field experiment.     

Eye light flashes on the Mir space station

The phenomenon of light flashes (LF) in eyes for people in space has been investigated onboard Mir. Data on particles hitting the eye have been collected with the SilEye detectors, and correlated with human observations. It is found that a nucleus in the radiation environment of Mir has roughly a 1% probability to cause an LF, whereas the proton probability is almost three orders of magnitude less. As a function of LET, the LF probability increases above 10 keV/micrometer, reaching about 5% at around 50 keV/micrometer.