A lossless compression algorithm for dual-polarization weather radar data based on prediction

With the development of dual-polarization weather radar technology, radar provides more and more products, and data accuracy continues to increase. The updating of detection performance also leads to a sharp increase in the amount of weather radar data. Data storage and transmission become an important issue to be solved in radar network applications. Data compression algorithms are used to reduce the amount of data transmitted and stored, but the characteristics of dual-polarization weather radar data are not fully considered in generic off-the-shelf data compression algorithms. This paper proposes a dual-polarization weather radar data compression algorithm (DPRC), which uses radial prediction to reduce the correlation of weather radar data and achieve efficient lossless compression of weather radar base data. The performance of the DPRC algorithm is evaluated using CSU-CHILL radar data. The experimental results show that the DPRC has a higher compression ratio than the generic off-the-shelf compression algorithm and is suitable for lossless compression of high resolution dual-polarization radar data.