PDF下载 分享
[1]沈邦跃,何建新,曾强宇.基于超分辨率的相控阵天气雷达数据压缩算法[J].成都信息工程大学学报,2023,38(06):621-629.[doi:10.16836/j.cnki.jcuit.2023.06.001]
　SHEN Bangyue,HE Jianxin,ZENG Qiangyu.Data Compression Algorithm of Phased Array Weather Radar based on Super Resolution[J].Journal of Chengdu University of Information Technology,2023,38(06):621-629.[doi:10.16836/j.cnki.jcuit.2023.06.001]
点击复制

基于超分辨率的相控阵天气雷达数据压缩算法

成都信息工程大学学报[ISSN:1006-6977/CN:61-1281/TN] 卷: 38 期数: 2023年06期 页码: 621-629 栏目: 电子信息科学与技术 出版日期: 2023-11-20
Title:
Data Compression Algorithm of Phased Array Weather Radar based on Super Resolution
文章编号:
2096-1618(2023)06-0621-09
作者:
沈邦跃1; 2;  何建新1; 2;  曾强宇1; 2
(1.成都信息工程大学电子工程学院，四川 成都 610225; 2.中国气象局大气探测重点开放实验室，四川 成都 610225)
Author(s):
SHEN Bangyue1; 2;  HE Jianxin1; 2;  ZENG Qiangyu1; 2
(1.College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China; 2.CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225, China)
关键词:
天气雷达;  相控阵雷达;  数据压缩;  帧内预测
Keywords:
weather radar;  phased array radar;  data compression;  predictive coding
分类号:
TN957.52
DOI:
10.16836/j.cnki.jcuit.2023.06.001
文献标志码:
A
摘要:
随着天气雷达技术不断进步，经过双偏振和相控阵两次技术发展，数据量急剧增长。爆发性增长的雷达数据量使数据传输和存储成为制约相控阵雷达业务化的瓶颈。提出相控阵天气雷达数据压缩算法，首先对数据进行下采样，对下采样数据进行预测编码得到预测残差，再将下采样数据进行超分辨率重建得到重建残差，组合预测残差和重建残差进行熵编码输出，实现数据无损压缩。使用江苏兴化CHARTOR-XPARD双偏振相控阵雷达数据对该算法进行评估，实验结果表明，该算法较通用算法压缩率更高，较次优算法压缩率提高15%～21%，适用于相控阵天气雷达数据无损压缩。
Abstract:
With the continuous progress of weather radar technology, the amount of data has increased dramatically after the development of dual polarization and phased array technology. The explosive growth of radar data makes data transmission and storage a problem to phased array radar business. In this paper, a data compression algorithm for phased array weather radar is proposed. First, the data is downsampled, and the downsampled data is predicted and encoded to obtain the prediction residuals. Then, the downsampled data is reconstructed to obtain the reconstruction residuals by super-resolution reconstruction. Combined with the prediction residuals and the reconstruction residuals, the entropy coding output is performed to achieve lossless data compression. The algorithm in this paper is evaluated using the data of Jiangsu Xinghua CHARTOR-XPARD dual polarization phased array radar. The results show that the algorithm in this paper has a higher compression rate than the general algorithm, and a 15%-21% higher compression rate than the sub optimal algorithm, which is suitable for lossless compression of phased array weather radar data.

参考文献/References:

[1] Liu X,An P,Chen Y,et al.An improved lossless image compression algorithm based on Huffman coding[J].Multimedia Tools and Applications,2021(1).
[2] Waleed M,Um T W,Khan A,et al.On the Utilization of Reversible Colour Transforms for Lossless 2-D Data Compression[J].Applied Sciences,2020,10(3):937.
[3] Xin GT,Fan P Y.Soft Compression for Lossless Image Coding Based on Shape Recognition[J].ENTROPY,2021,23:12.
[4] 陈威,李凤昌,章建军.基于小波零树的雷达回波数据的压缩[J].计算机工程与应用,2004,40(6):217-219.
[5] 潘志刚,王小龙,李志勇.SAR原始数据压缩的自适应比特分配BAQ算法[J].中国科学院大学学报,2017(1):106-111.
[6] 陈璐,马可,李重阳.一种气象雷达数据混合压缩算法[J].计算机与数字工程,2017,45(3):444-448.
[7] 李朋,刘小军,方广有.基于帧间差分的次表层探测雷达数据压缩[J].雷达科学与技术,2018,16(5):11-16.
[8] 黄云仙,马烁,艾未华.一种新的多普勒天气雷达回波数据无损压缩[J].解放军理工大学学报(自然科学版),2012,13(2):232-236.
[9] Zeng Q Y,He J X,Zhao S,et al.Weather Radar Data Compression Based on Spatial and Temporal Prediction[J].Atmosphere,2018,9(3):96.
[10] 夏正.基于预测算法的天气雷达回波数据压缩编码研究[D].南昌:南昌航空大学,2019.
[11] 曾强宇,Chandrasekar V.基于预测的双线偏振天气雷达数据无损压缩算法[J].气象学报,2019,77(2):346-357.
[12] 张蔚然,吴翀,刘黎平.双偏振相控阵雷达与业务雷达的定量对比及观测精度研究[J].高原气象,2021,40(2):424-435.
[13] 刘黎平,胡志群,吴翀.双线偏振雷达和相控阵天气雷达技术的发展和应用[J].气象科技进展,2016,6(3):28-33.
[14] 何建新,任红萍,曾强宇,等.基于改进全变差的天气雷达回波超分辨率重建[J].计算机仿真,2014,31(7):5.
[15] Lakshmanan V.Lossless coding and compression of radar reflectivity data[C].Munich:30th Int.Conf.Radar Meteorol,2001.

相似文献/References:

[1]王翔弘,何建新,王 旭,等.太原CINRAD/CC雷达与X波段雷达观测一致性分析[J].成都信息工程大学学报,2018,(03):236.[doi:10.16836/j.cnki.jcuit.2018.03.003]
　WANG Xiang-hong,HE Jian-xin,WANG Xu,et al.Observation Consistency Analysis of the Taiyuan CINRAD/CCWeather Radar and the X-band Radar[J].Journal of Chengdu University of Information Technology,2018,(06):236.[doi:10.16836/j.cnki.jcuit.2018.03.003]
[2]王海江,刘玟宏,邓洋洋,等.S 波段多普勒天气雷达回波模拟[J].成都信息工程大学学报,2016,(01):12.
　WANG Hai-jiang,LIU Wen-hong,DENG Yang-yang,et al.S Band Doppler Weather Radar Echo Simulation[J].Journal of Chengdu University of Information Technology,2016,(06):12.
[3]张 双,张福贵,杨金红.负仰角观测对新一代天气雷达( CINRAD) 探测降水的意义[J].成都信息工程大学学报,2016,(01):49.
　ZHANG Shuang,ZHANG Fu-gui,YANG Jin-hong.The Significance of Negative Elevation Observation to the Precipitation of the New Generation Weather Radar[J].Journal of Chengdu University of Information Technology,2016,(06):49.
[4]赵 亮.龙卷过程中雷达合成切变产品的分析[J].成都信息工程大学学报,2017,(03):269.[doi:10.16836/j.cnki.jcuit.2017.03.007]
　ZHAO Liang.Analysis of Radar Composite Shear Products in the Process of Tornado[J].Journal of Chengdu University of Information Technology,2017,(06):269.[doi:10.16836/j.cnki.jcuit.2017.03.007]
[5]蒋秋菲,王 旭,何建新,等.天气雷达遮挡区域识别[J].成都信息工程大学学报,2017,(05):469.[doi:10.16836/j.cnki.jcuit.2017.05.001]
　JIANG Qiu-fei,WANG Xu,HE Jian-xin,et al.Identification of Weather Radar Shielding Region[J].Journal of Chengdu University of Information Technology,2017,(06):469.[doi:10.16836/j.cnki.jcuit.2017.05.001]
[6]周淑玥,李 静,鲜 林,等.基于数字高程模型和反射率因子垂直廓线的天气雷达波束遮挡订正算法[J].成都信息工程大学学报,2023,38(05):497.[doi:10.16836/j.cnki.jcuit.2023.05.001]
　ZHOU Shuyue,LI Jing,XIAN Lin,et al.Weather Radar Beam Block Correction Algorithm based on DEM Model and Vertical Profile of Reflectivity[J].Journal of Chengdu University of Information Technology,2023,38(06):497.[doi:10.16836/j.cnki.jcuit.2023.05.001]

备注/Memo

收稿日期:2022-10-12
基金项目:四川省科技厅中央引导地方科技发展基金资助项目(2020 ZYD051)

更新日期/Last Update: 2023-12-10