Dropouts Processing in ADS-B Real-time Monitoring Based on Hybrid Filtering

doi:10.16182/j.issn1004731x.joss.201809029

Abstract

Abstract: Due to the bad real-time performance of variable dimension Kalman filter in dealing with the leakage of ADS-B real-time monitoring, a position/speed hybrid filter method is proposed. The variable dimension Kalman filter is improved based on the characteristic that the position message and the velocity message of ADS-B message are sent at different time. Two measurement equations for position and speed are designed, and different measurement equation is selected according to message category. The speed/position and navigation accuracy category in message is utilized to estimate the position/speed of present moment, so as to effectively solve the problem of data dropouts. Experimental results show that compared with the variable dimension Kalman filter, the track time interval processed by the proposed methodis closer to the information transmission cycle of one second and has less impact on the delay.

Key words: ADS-B, dropouts, hybrid filtering, Kalman filter, real-time monitor

CLC Number:

TP391.9

Shen Xiaoyun, Shen Jinxing, Zhang Siyuan, Jiao Weidong. Dropouts Processing in ADS-B Real-time Monitoring Based on Hybrid Filtering[J]. Journal of System Simulation, 2018, 30(9): 3457-3463.

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