Analysis to Data Processing Method in Differential Barometric Altimeter

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Abstract:

Differential barometric altimeter is with good accuracy in positioning system. There is different elevation accuracy with one type sensor under different filtering models. We compare application performance between the variable weighted Kalman filter and the least-squares fitting of data processing in the differential barometric altimetry system. Experiments show that Kalman filtering is more suitable for measuring high dynamic model and least-squares fitting way is more suitable in a static altimeter model.

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448-451

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September 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Z. Q. Hu, L. R. Zhang, Barometric altimeter in wireless communication network indoor positioning system [J], Journal of Beijing Institute of Technology, 2013, 22(3): 380-386.

Google Scholar

[2] L. R. Zhang, L. R. Ma, H. F. Ji, et al., Positioning Accuracy of CAPS Subject to Earth Height Constraint [C], the 2nd China Satellite Navigation Conference, 2011, 1277-1281.

Google Scholar

[3] Y. Zhang, C. H. Qu. An Algorithm associated with Least Square (LS) and Adaptive Kalman Filtering [J]. Fire Control Radar Technology, 2008, 37(4): 19-22.

Google Scholar

[4] P. R. Wolf, C. D. Ghilani. Adjust Computations: Statistics and Least Squares in Surveying and GIS[M]. John: Wiley & Sons, Inc (1997).

Google Scholar

[5] K. L. Ding, Y. Z. Sheng, J. K. Ou. Methods of line-fitting based on total least-squares [J]. Journal of Liaoning Technical University (Natural Science), 2010, 29(1): 44-47.

Google Scholar