Estimation methods for GPS kinematic data processing

Gang Chen; Xiong Pan

doi:10.1117/12.836652

10 July 2009 Estimation methods for GPS kinematic data processing

Gang Chen, Xiong Pan

Proceedings Volume 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering; 74910V (2009) https://doi.org/10.1117/12.836652
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China

Abstract

The characteristics of three GPS kinematical data processing models, Least Square, Kalman filtering, and Semiparametric model are discussed and their advantages and disadvantages are compared. With observational data and pertinent data processing software, the applicable condition, context and effect of the three models are experimented. Results show that when the mobile platform is in uniform motion, the accuracy of the three models are almost equal; when the mobile platform is in stochastic acceleration, the accuracy of Semiparametric model is superior to that of LS, and that of Kalman filtering is the worst.

Citation Download Citation

Gang Chen and Xiong Pan "Estimation methods for GPS kinematic data processing", Proc. SPIE 7491, PIAGENG 2009: Remote Sensing and Geoscience for Agricultural Engineering, 74910V (10 July 2009); https://doi.org/10.1117/12.836652

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