POBI interpolation algorithm for CYGNSS near real time flood detection research: A case study of extreme precipitation events in Henan,China in 2021

In late 2016, NASA launched the first constellation of the global navigation satellite system reflectometry (GNSS-R) small satellites called the Cyclone Global Navigation Satellite System (CYGNSS). The stable data quality and continuous free availability of CYGNSS scientific data provided a new method for flood monitoring. However, owing to the pseudorandom distribution of CYGNSS data, researchers must always choose between high temporal resolution and high spatial resolution during the performance of flood monitoring based on CYGNSS data. For floods caused by extreme precipitation with sudden and short durations, the current flood mapping based on CYGNSS data cannot be updated in near real time. However, the near real time update of the flood distribution range is meaningful for postdisaster emergency response and rapid rescue. This study aimed to address this problem using a newly proposed spatial interpolation method based on previously observed behaviour (POBI). First, a method for calculating the surface reflectivity of the CYGNSS was introduced, followed by the principle of the POBI spatial interpolation method. The applicability of the POBI method in Henan Province, China, was then analysed, and by using the flood in Henan Province, China, in July 2021 as an example, the feasibility of CYGNSS near real time flood mapping based on the POBI method was evaluated. Based on the results, near real time and 3 km flood distribution monitoring results can be obtained using the proposed new method. The results were evaluated using MODIS (Moderate Resolution Imaging Spectroradiometer) images and compared with the observations of SMAP (Soil Moisture Active Passive) and GPM (Global Precipitation Measurement) in the same period. The results show that the flooded areas obtained by CYGNSS correspond to the inundated areas in MODIS images and are also in high agreement with the SMAP. In addition, CYGNSS allows for finer mapping and quantification of inundation areas and flood duration. Moreover, we also discussed the potential of CYGNSS to detect floods in shorter periods of time (a few hours) and did a preliminary evaluation using precipitation data from meteorological stations. The results are also highly consistent.     

地面放射性测量模型γ剂量率值空间分布规律研究

地面模型是根据IAEA174号报告研建的用于校准便携式γ能谱仪、γ辐射仪的计量标准装置，最初主要用于地质勘查。2016年至2018年，新研建了钾含量30 %（YK3）和铀含量1 %（YU4）的两个模型，并确定了模型量值。远离模型表面中心位置的剂量率较低，随着中心点的接近，剂量率逐渐上升，YK3和YU4的剂量率坪区分别为模型中心点及周围半径约40 cm和50 cm范围内，在坪区内剂量率变化均不大于0.6 %；在参考点3.0 cm上的剂量率分别为320.8 nGy·h^-1和4.3×10⁴ nGy·h^-1；超过3.0 cm时，剂量率随高度呈非线性变化；根据不同高度上的理论计算和实测结果比对，在40 cm高度实测范围以内，YK3实测结果与理论计算结果相对偏差在3 %范围以内，120 cm高度实测范围内，YU4实测结果与理论计算结果相对偏差在2 %范围以内。     

未知纬度条件下基于空间圆拟合的SINS初始对准方法

传统的捷联惯导系统(SINS)晃动基座初始对准算法,如积分双矢量方法和多矢量Wahba方法等均需要精确的纬度信息,粗对准偏航角误差较大.针对此特点,提出了一种未知纬度条件下基于空间圆拟合的SINS初始对准方法.根据重力矢量在惯性系中绕地轴旋转包含北向信息的特征,以初始时刻凝固载体坐标系作为惯性系,首先对重力矢量在凝固载体系内进行投影并滤波,对其矢量端点进行空间圆拟合,然后通过三角几何关系得到导航坐标系,从而完成对准过程.通过仿真验证,证实了该对准方法不需要已知对准点的精确位置信息,相比于积分双矢量方法与多矢量Wahba方法,偏航角对准精度分别提高了12.37'与5.10'.