ON-SITE DATA-PROCESSING ALGORITHM AND OPTIMIZATION FOR AIRBORNE ICE SOUNDING RADAR CONFIGURED ON THE “SNOW EAGLE 601”

ON-SITE DATA-PROCESSING ALGORITHM AND OPTIMIZATION FOR AIRBORNE ICE SOUNDING RADAR CONFIGURED ON THE “SNOW EAGLE 601”
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DOI：
10.5194/isprs-archives-xliii-b3-2021-449-2021
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发表时间：
2021
期刊：
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影响因子：
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通讯作者：
X. Cui;S. Lang;L. Li;B. Sun
X. Cui;S. Lang;L. Li;B. Sun
中科院分区：
其他
文献类型：
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作者：
X. Cui;S. Lang;L. Li;B. Sun

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航空观测是在遥远、恶劣的南极地区收集资料、研究南极与全球气候关系的重要途径。在航空观测过程中，需要在现场进行数据处理和质量控制，以便及时评估机载仪器的状态，提供科学线索，为后续的航空观测制定理想的方案。机载冰情探测雷达是机载仪器的重要组成部分，它可以探测到冰下基岩的地形和内部结构，这是其他仪器无法实现的。针对我国第一架南极固定翼飞机“雪鹰601”获得的高分辨率、高信噪比（SNR）探冰雷达数据，提出了一种现场数据处理算法。此外，在静态预分配内存、数据并行分块处理等方面对算法进行了进一步优化，提高了处理速度，满足了现场数据质量控制和分析的要求。最后，通过在不同的计算机配置（包括i7、i5 CPU和8G、16G内存，同一个磁盘）上的实现，对优化后的算法进行了不同数据量的冰情探测雷达数据测试。结果表明，在不同的计算机配置下，优化算法的平均处理速度是未优化算法的5.143倍。* 通讯作者
Airborne observation is an important approach to collect data in the remote, hostile Antarctica and study the relationship between the Antarctica and global climate. During airborne observations, it is necessary to conduct data processing and quality control on site, which can help to timely evaluate the status of airborne instruments, provide scientific clues, and develop ideal schemes for following airborne observations. As one critical component of airborne instruments, airborne ice sounding radar can delineate sub-ice bedrock topography and internal layers, which cannot be realized by other instruments. In this study, we present an on-site data processing algorithm for high-resolution and high signal-to-noise ratio (SNR) ice sounding radar data acquired by the “Snow Eagle 601”, the first fixed-wing airplane deployed by China for the Antarctic expeditions. In addition, the algorithm is further optimized in terms of static pre-allocated memory and parallel and block processing of data to enhance processing speed and meet the requirements for quality control and analysis of on-site data. Finally, we test the optimized algorithm with different volume of ice sounding radar data through implementing on different computer configurations, including i7, i5 CPU and 8G, 16G memory with the same disk. The results show that the average processing speed of the optimized algorithm is 5.143 times faster than the nonoptimized algorithm on different computer configurations. * Corresponding author