Abstract
Abstract. 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 non-optimized algorithm on different computer configurations.
Highlights
In the context of global warming, it is critical to monitor and assess changes in polar ice sheets as well as their impact on global climate and sea level (Kennicutt et al, 2014)
The airborne ice sounding radar system is functionally similar to the High-Capability Radar Sounder (HiCARS) system, a phasecoherent radar system developed by the University of Texas, Institute for Geophysics (UTIG)
The traditional orthogonal detection is completed by a phase detector, which requires the receiver to be equipped with an analog mixer and a low-pass filter (LPF)
Summary
In the context of global warming, it is critical to monitor and assess changes in polar ice sheets as well as their impact on global climate and sea level (Kennicutt et al, 2014). Because airborne platforms have the advantages of high data-acquisition efficiency and wide coverage, aerogeophysical surveys featuring synchronized observations achieved by multiple scientific instruments have become an indispensable means of data collection in polar regions. Airborne ice sounding radar, with deep penetrating capability in ice, has been widely used in investigating the polar ice sheets since the 1960s (Waite and Schmidt, 1962). In 2015, China deployed the “Snow Eagle 601”, a BT-67 airplane for the Antarctic expeditions, on which a similar version of ice sounding radar with the High-Capability Radar Sounder (HiCARS) was configured (Cui et al, 2018). We introduce the radar system configured on the “Snow Eagle 601” and data acquisition firstly, and present the developed on-site processing algorithm for radar data secondly. We introduce the optimization of the algorithm in detail, and give out the test results
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