Next Generation Geostationary Imager & Sounder Compression Algorithms

As space-based remote sensing technologies grow in capability, the amount of data collected by next-generation geosynchronous orbiting weather instruments will substantially increase, requiring new data compression techniques to be applied to downlink the data from the satellite to the ground within available bandwidth constraints. This paper presents new data compression techniques developed for compression of next-generation geosynchronous imager data and next-generation geosynchronous sounder data.

L3Harris’ next-generation weather imagers will use a combination of lossy and lossless compression algorithms for their 18 spectral bands. While many of the infrared bands will be compressed in a lossless manner using the CCSDS 121.0 standard, some of the higher resolution visible and near-infrared bands will use an L3Harris-developed, lossy compression that is achieved through adaptations to the CCSDS 122.0 standard wavelets and application of the CCSDS 121.0 standard encoder. L3Harris’ next-generation hyperspectral sounders will use a novel algorithm to compress the interferograms produced by its Fourier transform spectrometer (FTS) architecture. This newly patented L3Harris compression algorithm applies the theory of principal components with encoding of the residual differences using lossless Huffman encoding. Though not planned for near-term use, the algorithm is extensible to lossy interferogram compression by quantizing the residual differences before encoding. High-level descriptions of these compression algorithms will be described with a focus on optimizing available bandwidth while also providing the highest possible data quality for use by the weather community.