Compression algorithm for infrared hyperspectral sounder data

Abstract

Summary form only given. The research is undertaken by NOAA/NESDIS, for its GOES-R Earth observation satellite series, to be launched in the 2013 time frame, to enable greater distribution of its scientific data, both within the US and internationally. We have developed a new lossless algorithm for compression of the signals from NOAA's environmental satellites using current spacecraft to simulate data from the upcoming GOES-R instrument, and focusing on Aqua Spacecraft's AIRS (atmospheric infrared sounder) instrument in our case study. The AIRS is a high resolution instrument which measures infrared radiances at 2378 wavelengths ranging from 3.74-15.4 /spl mu/m. The AIRS takes 90 measurements as it scans 48.95 degrees perpendicular to the satellite's orbit every 2.667 seconds. We use Level 1A digital count data granules, which represent 6 minutes (or 135 scans) of measurements. Therefore, our data set consists of a 90/spl times/135/spl times/1502 cube of integers ranging from 12-14 bits. Our compression algorithm consists of the following steps: 1) channel partitioning; 2) adaptive clustering; 3) projection onto principal directions; 4) entropy coding of the residuals.