An autonomous receiver/digital signal processor applied to ground‐based and rocket‐borne wave experiments

Abstract

The programmable combined receiver/digital signal processor platform presented in this article is designed for digital downsampling and processing of general waveform inputs with a 66 MHz initial sampling rate and multi‐input synchronized sampling. Systems based on this platform are capable of fully autonomous low‐power operation, can be programmed to preprocess and filter the data for preselection and reduction, and may output to a diverse array of transmission or telemetry media. We describe three versions of this system, one for deployment on sounding rockets and two for ground‐based applications. The rocket system was flown on the Correlation of High‐Frequency and Auroral Roar Measurements (CHARM)‐II mission launched from Poker Flat Research Range, Alaska, in 2010. It measured auroral “roar” signals at 2.60 MHz. The ground‐based systems have been deployed at Sondrestrom, Greenland, and South Pole Station, Antarctica. The Greenland system synchronously samples signals from three spaced antennas providing direction finding of 0–5 MHz waves. It has successfully measured auroral signals and man‐made broadcast signals. The South Pole system synchronously samples signals from two crossed antennas, providing polarization information. It has successfully measured the polarization of auroral kilometric radiation‐like signals as well as auroral hiss. Further systems are in development for future rocket missions and for installation in Antarctic Automatic Geophysical Observatories.

Properties of the Stimulated Electromagnetic Emissions During the Inclined High‐Frequency Pumping of the Ionosphere Near the Fourth Electron Gyroharmonic at the High‐Frequency Active Auroral Research Program Facility

“…The dynamic range of the instruments is estimated to be better than 90 dB. For details about equipment on site C, see Dombrowski et al (2016).…”

Key Technologies of Steel Plate Surface Defect Detection System Based on Artificial Intelligence Machine Vision

“…Choudhary et al have developed an online automatic detection system for surface defects of continuous casting billets, which has set off a research boom in infrared detection of surface defects [7]. Dombrowski et al chose a fully programmable image digitizer and a fully programmable high-speed digital signal processor to process digital image signals and used the system for cold-rolled strip steel surface, edge cracks, and other edge tests [8]. Shu et al conducted the research on the strip steel surface detection system which analyzes the CCD detection method and proposes some effective algorithms [9].…”