基于多智能体导航的高超飞行器信息融合方法

doi:10.3969/j.issn.1001-506X.2020.02.20

Abstract

Abstract:

Precise navigation technology is the key to performing the important function for hypersonic vehicle (HV). However, the high Mach number and strong maneuverability make the navigation system error and make the observation noise of HV hard to be accurately described, so as to constrain the navigation information accuracy and real-time performance. In order to obtain high precision navigation information in time, the Kalman filter algorithm based on the set membership framework is proposed. On the one hand the multi-agent distributed cooperative detection is adopted to get the intersection of observation ellipsoid, which improves the observation efficiency and measurement accuracy. On the other hand, two kinds of error models are designed and used to solve the minimum mean square error together of the state estimation in order to calculate the filtering gain. The anti-disturbance ability of the proposed algorithm to noise is improved and the mean square error of the state estimation can reach the minimum value. Through digital simulation, the proposed method is applied to the navigation model compared with the state estimation of the extended Kalman filter and set-membership filter. The results show that the proposed algorithm has a higher estimation accuracy under different noise influences. It is expected that the research results will provide new technical support for real-time precise navigation of HV, and have important theoretical significance and application value for HV.

Key words: information fusion, Kalman filter, set-membership estimation, multi-agent, hypersonic vehicle (HV)

CLC Number:

U491

Yan ZHAO, Jianfeng WU, Yupeng GAO. Information fusion method of hypersonic vehicle based on multi-agent navigation[J]. Systems Engineering and Electronics, 2020, 42(2): 405-413.

Figures/Tables 12

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算法	东向位置误差/m		北向位置误差/m		天向位置误差/m
算法	均值	标准差	均值	标准差	均值	标准差
EKF	67.25	215.32	61.08	184.39	67.57	236.86
SMF	46.50	92.31	32.4	83.58	43.80	138.03
SMKF	27.12	47.18	25.36	41.51	25.03	47.16

算法	计算时间/s
EKF	0.283
SMF	0.197
SMKF	0.315

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Information fusion method of hypersonic vehicle based on multi-agent navigation

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