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捷联式航空重力扰动矢量解算及误差补偿

The Solution and Error Compensation of Strapdown Airborne Gravity Disturbance Vector
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摘要 介绍捷联式航空重力矢量测量的基本原理,利用波数相关滤波(WCF)、比力线性校正的方法对重力扰动的水平和垂向分量进行误差补偿,评定内符合精度。对国产捷联式航空重力矢量仪的某次试验数据进行处理,以验证和评估航空重力矢量仪的性能。结果表明,在半波长分辨率为7.5km时,6条重复测线的重力扰动水平分量经波数相关滤波处理后,东、北向分量的平均内符合精度分别从9.77mGal、9.18mGal提高到5.95mGal、3.83mGal;对比力的垂向分量线性校正后,将解算的重力扰动垂向分量再用WCF方法处理,其平均内符合精度从1.27mGal提高到0.59mGal。 This paper introduces the basic principle of strapdown airborne gravity vector measurement,and uses wavenumber correlation filtering(WCF)and specific force linearity correction method to compensate the horizontal and vertical components of gravity disturbance.It then evaluates the internal accuracy.The test data of the domestic strapdown airborne vector gravimeter is processed and analyzed to verify and evaluate the performance of airborne vector gravimeter.The results show that after applying wavenumber correlation filter for the horizontal component of gravity disturbance of the six repeatlines,the average internal accuracy of the east and the north components increases from 9.77 mGal and 9.18 mGal,to 5.95 mGal and 3.83 mGal,respectively,with half-wavelength resolution of 7.5 km.After linear correction for the vertical component of specific force,WCF method is used to process the vertical component of gravity disturbance of the repeatlines.The average internal accuracy of the vertical component of gravity disturbance is improved from 1.27 mGal to 0.59 mGal.
作者 郭栋 孙中苗 吴富梅 张琪 GUO Dong;SUN Zhongmiao;WU Fumei;ZHANG Qi(State Key Laboratory of Geo-Information Engineering,1 Mid-Yanta Road,Xi’an 710054,China;Xi’an Research Institute of Surveying and Mapping,1 Mid-Yanta Road,Xi’an 710054,China;School of Geological Engineering and Geomatics,Chang’an University,126 Yanta Road,Xi’an 710054,China)
出处 《大地测量与地球动力学》 CSCD 北大核心 2018年第12期1295-1301,共7页 Journal of Geodesy and Geodynamics
基金 国家自然科学基金(41774018 41374003)~~
关键词 航空矢量重力测量 卡尔曼滤波 波数相关滤波 重力扰动矢量 线性校正 airborne vector gravimetry Kalman filter wavenumber correlation filter gravity disturbance vector linear correction
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