ADS-B track filtering and processing based on the"current"statistical model
To address the accuracy problem of ADS-B track processing,a method of ADS-B track filtering and processing is proposed.Firstly,the process of ADS-B track processing is introduced.Secondly,for the accuracy problem in ADS-B track processing,the"current"statistical model is introduced for research.Then,based on the"current"statistical model,the adaptive filtering algorithm is used for track prediction to achieve track smoothing.Finally,through comparative simulation experiments,the track filtering and processing performance of the adaptive filtering algorithm is analyzed,and the processing effect of the Kal-man filtering algorithm and the adaptive filtering algorithm on the track,as well as the mean value error of the two algorithms are compared.The results show that the adaptive filtering algorithm based on the"cur-rent"statistical model has a good effect on the track processing,and can effectively achieve track smoothing and prediction.
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