Acta Optica Sinica, Volume. 44, Issue 24, 2428005(2024)
Hierarchical Motion Estimation of Spatially Destabilized Targets under Gaussian Mixture Models
Fig. 2. Comparison of the average estimation errors for different frame number of point clouds
Fig. 3. Still point cloud images under different noise intensities. (a) Satellite A; (b) satellite B
Fig. 4. Comparative analysis of the estimation errors of motion parameters by DRM[15], RPM[16], TM[10], and proposed method for different motion states. (a) Error of spin angular velocity; (b) error of initial spin axis; (c) error of precession angular velocity; (d) error of precession axis
Fig. 5. Analysis of the estimation errors of DRM[15], RPM[16], TM[10], and proposed method for motion parameters under different Gaussian noise standard deviations for satellite A for 252 different motion states. (a) Mean error of spin angular velocity; (b) mean error of precession location; (c) mean error of initial spin axis; (d) mean error of precession angular velocity; (e) mean error of precession axis
Fig. 6. Motion parameters in the point cloud sequence of satellite B are solved using DRM[15], RPM[16], TM[10], and proposed method, the point clouds of the first and fifth frames are then mapped to the reference time for comparative analysis. (a) Noiseless; (b) 0.5% noise; (c) 1.0% noise; (d) 1.5% noise
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Zhiqiang Zhou, Riming Sun, Chenglong Guo, Yilong Zhu. Hierarchical Motion Estimation of Spatially Destabilized Targets under Gaussian Mixture Models[J]. Acta Optica Sinica, 2024, 44(24): 2428005
Category: Remote Sensing and Sensors
Received: Mar. 14, 2024
Accepted: May. 13, 2024
Published Online: Dec. 13, 2024
The Author Email: Sun Riming (sunriming78@126.com)
CSTR:32393.14.AOS240731