基于预测的双线偏振天气雷达数据无损压缩算法

随着双线偏振天气雷达技术的发展，雷达提供的探测参量越来越多，数据精度不断提高。探测性能提升使得天气雷达数据量急剧增长，数据存储和传输是雷达网络化应用中需要解决的重要问题。数据压缩算法用于减小传输和存储的数据量，但通用的数据压缩算法并未充分考虑双线偏振天气雷达数据的特点。文中提出适用于双线偏振天气雷达数据压缩算法（DPRC），使用径向预测减小天气雷达数据相关性，实现了天气雷达基数据的高效无损压缩。使用CSU-CHILL雷达数据和双线偏振改造后的CINRAD SA雷达对DPRC的算法性能进行评估，试验结果表明，DPRC较通用的压缩算法压缩率更高，适用于高分辨率双线偏振雷达数据无损压缩。 

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.