Alluvial architecture in headwater streams with special emphasis on step–pool topography

Alluvial mountain streams exhibit a range of channel forms: pool–riffle, plane bed, step–pool and cascades. Previous work suggested that these forms exist within discrete, and progressively steeper slope classes. Measurements conducted at over 100 sites in west‐central and central Idaho confirm that slope steepens progressively as one moves from pool–riffle, to plane bed, to step–pool, and finally to cascades. Median slope for pool–riffle topography is 0·0060, for plane beds 0·013, for step–pools 0·044, and for cascades 0·068. There is substantial overlap in the slopes associated with these channel forms. Pool–riffle topography was found at slopes between 0·0010 and 0·015, plane beds between 0·0010 and 0·035, step–pools between 0·015 and 0·134, and cascades between 0·050 and 0·12. Step–pools are particularly striking features in headwater streams. They are characterized by alternating steep and gentle channel segments. The steep segments (step risers) are transverse accumulations of boulder and cobbles, while the gentle segments (pools) contain finer material. Step wavelength is best correlated to step height which is in turn best correlated to the median particle size found on step risers. This result differs from past studies that have reported channel slope to be the dominant control on step wavelength. The presumed geometry and Froude number associated with the features under formative conditions are consistent with the existence field for antidunes and by extension with the hypothesis that step–pools are formed by antidunes. Copyright © 2000 John Wiley & Sons, Ltd.     

Wide-field ultraviolet imager for astronomical transient studies

Though the ultraviolet (UV) domain plays a vital role in the studies of astronomical transient events, the UV time-domain sky remains largely unexplored. We have designed a wide-field UV imager that can be flown on a range of available platforms, such as high-altitude balloons, CubeSats, and larger space missions. The major scientific goals are the variability of astronomical sources, detection of transients such as supernovae, novae, tidal disruption events, and characterizing active galactic nuclei variability. The instrument has a 80 mm aperture with a circular field of view of 10.8 degrees, an angular resolution of ～22 arcsec, and a 240 - 390 nm spectral observation window. The detector for the instrument is a Microchannel Plate (MCP)-based image intensifier with both photon counting and integration capabilities. An FPGA-based detector readout mechanism and real time data processing have been implemented. The imager is designed in such a way that its lightweight and compact nature are well fitted for the CubeSat dimensions. Here we present various design and developmental aspects of this UV wide-field transient explorer.     

A software package for evaluating the performance of a star sensor operation

We have developed a low-cost off-the-shelf component star sensor (StarSense) for use in minisatellites and CubeSats to determine the attitude of a satellite in orbit. StarSense is an imaging camera with a limiting magnitude of 6.5, which extracts information from star patterns it records in the images. The star sensor implements a centroiding algorithm to find centroids of the stars in the image, a Geometric Voting algorithm for star pattern identification, and a QUEST algorithm for attitude quaternion calculation. Here, we describe the software package to evaluate the performance of these algorithms as a star sensor single operating system. We simulate the ideal case where sky background and instrument errors are omitted, and a more realistic case where noise and camera parameters are added to the simulated images. We evaluate such performance parameters of the algorithms as attitude accuracy, calculation time, required memory, star catalog size, sky coverage, etc., and estimate the errors introduced by each algorithm. This software package is written for use in MATLAB. The testing is parametrized for different hardware parameters, such as the focal length of the imaging setup, the field of view (FOV) of the camera, angle measurement accuracy, distortion effects, etc., and therefore, can be applied to evaluate the performance of such algorithms in any star sensor. For its hardware implementation on our StarSense, we are currently porting the codes in form of functions written in C. This is done keeping in view its easy implementation on any star sensor electronics hardware.