钱妮佳Nijia Qian
所在单位：环境与测绘学院
学历：博士研究生毕业
在职信息：在岗
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Bridging the Terrestrial Water Storage Anomalies between the GRACE/GRACE-FO Gap Using BEAST + GMDH Algorithm[J].Remote Sensing,2024,16(19)
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凤勇, 常国宾*, 钱妮佳, 等(2023). GRACE Level-2数据的RTS状态平滑[J].测绘学报,2023,52(11):1858-1872
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Nijia Qian, Guobin Chang*, Jingxiang Gao, et al. (2022). Adaptive DDK filter for GRACE time-variable gravity field with a novel anisotropic filtering strength metric[J].remote sensing,2022,14(13)
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Nijia Qian, Guobin Chang*, Pavel Ditmar, Jingxiang Gao, et al. (2022). Sparse DDK: A Data-Driven Decorrelation Filter for GRACE Level-2 Products[J].Remote Sensing,2022,14(12)
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Guobin Chang*, Nijia Qian, Shaofeng Bian. (2023). Statistically optimal estimation of surface mass anomalies by directly using GRACE level-2 spherical harmonic coefficients as measurements[J].Geophysical Journal International,2022,233(3):1786-1799
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Cheng Pan, Nijia Qian, Zengke Li, Jingxiang Gao*, et al. (2021). A Robust Adaptive Cubature Kalman Filter Based on SVD for Dual-Antenna GNSS/MIMU Tightly Coupled Integration[J].Remote Sensing,2021,13(10)
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Nijia Qian, Guobin Chang*, Jingxiang Gao, Cheng Pan, et al. (2021). Vehicle's Instantaneous Velocity Reconstruction by Combining GNSS Doppler and Carrier Phase Measurements through Tikhonov Regularized Kernel Learning[J].IEEE Transactions on Vehicular Technology,2021,70(5):4190-4202
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Nijia Qian, Guobin Chang*. (2021). Optimal filtering for state space model with time-integral measurements[J].Measurement,2021,176
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Liu Yang, Guobin Chang*, Nijia Qian, Jingxiang Gao. (2020). Improved atmospheric weighted mean temperature modeling using sparse kernel learning[J].GPS Solutions,2021,25(1)
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Nijia Qian, Guobin Chang*, Jingxiang Gao. (2020). Smoothing for continuous dynamical state space models with sampled system coefficients based on sparse kernel learning[J].Nonlinear Dynamics,2020,100(4):3597-3610
