Distributed adaptive Kalman filter based on variational Bayesian technique

作者：Hu, Chen^*; Hu, Xiaoming; Hong, Yiguang

来源：Control Theory and Technology, 2019, 17(1): 37-47.

DOI：10.1007/s11768-019-8183-9

• Adaptive kalman filter
• Consensus algorithms
• Distributed Kalman filters
• Distributed target tracking
• Multiagent networks
• Posterior distributions
• Variational bayesian
• Wishart distribution

In this paper, distributed Kalman filter design is studied for linear dynamics with unknown measurement noise variance, which modeled by Wishart distribution. To solve the problem in a multi-agent network, a distributed adaptive Kalman filter is proposed with the help of variational Bayesian, where the posterior distribution of joint state and noise variance is approximated by a free-form distribution. The convergence of the proposed algorithm is proved in two main steps: noise statistics is estimated, where each agent only use its local information in variational Bayesian expectation (VB-E) step, and state is estimated by a consensus algorithm in variational Bayesian maximum (VB-M) step. Finally, a distributed target tracking problem is investigated with simulations for illustration.

• 出版日期2019-2-1
• 单位中国科学院大学