Low-cost object tracking with MEMS sensors, Kalman filtering and simplified two-filter-smoothing
暂无分享,去创建一个
[1] G.F. Trommer,et al. Post-processing GNSS/INS Measurements Using a Tightly Coupled Fixed-Interval Smoother Performing Carrier Phase Ambiguity Resolution , 2006, 2006 IEEE/ION Position, Location, And Navigation Symposium.
[2] G. Schmidt,et al. Inertial sensor technology trends , 2001 .
[3] T. Başar,et al. A New Approach to Linear Filtering and Prediction Problems , 2001 .
[4] Xin Xu,et al. An Approach to Improving Attitude Estimation Using Sensor Fusion for Robot Navigation , 2011 .
[5] W. F. Phillips,et al. Review of Attitude Representations Used for Aircraft Kinematics , 2001 .
[6] Chris Hide,et al. GPS and Low Cost INS Integration for Positioning in the Urban Environment , 2005 .
[7] D. M. Bevly,et al. Characterization of Inertial Sensor Measurements for Navigation Performance Analysis , 2006 .
[8] Arthur Gelb,et al. Applied Optimal Estimation , 1974 .
[9] Markus Haid,et al. Low cost inertial orientation tracking with Kalman filter , 2004, Appl. Math. Comput..
[10] M. Shuster. A survey of attitude representation , 1993 .
[11] Malcolm D. Shuster. Survey of attitude representations , 1993 .
[12] C. Striebel,et al. On the maximum likelihood estimates for linear dynamic systems , 1965 .