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《Science of Surveying and Mapping》 2013-03
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A study on smoothing algorithm based on Bayes estimation

SONG Chao,HAO Jin-ming(Institute of Surveying and Mapping,Information Engineering University,Zhengzhou 450052,China)  
A smoothing algorithm is based on Bayesian theory,which should be derived using the Kalman filtering.In the case of post-process,the precision can be improved by estimation using observations from past to future.The filter algorithm uses the observations from past to now.So,in theory,the smoothing algorithm is better than the filter algorithm in precision.Two simulation experiments were taken in the paper,and the results showed that the smoothing algorithm is more effective than Kalman filtering and a weighted combination of forward and backward filtering.
【Fund】: 信息工程大学测绘学院硕士学位论文创优基金(201112)
【CateGory Index】: P207
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