Augmented information filter based on cooperative navigation algorithm for unmanned surface vessels

作者：Xu, Bo; Xiao, Yongping; Chi, Shanshan; Wang, Wenjia

来源：Journal of Computational Information Systems, 2014, 10(1): 239-249.

DOI：10.12733/jcis8763

• Augment state
• Colocations
• Cooperative navigations
• Information matrix
• Joint distributions
• Sparse matrices
• Unmanned surface vessels

To the problems of computational complexity for the regular method about cooperative navigation such as KF and EKF, the paper uses augmented information filter to study cooperative navigation for unmanned surface vessels. It uses information parameter to augment states and update observations, then recovers the status and covariance. This method preserves the historical states in the filter, thus the joint distribution of the information matrix is sparse and computational complexity of filter is less. And augmenting states and updating observations is local, which is convenient to distribute the work. The simulation result indicates that the method ensures these performance advantages and guarantees the estimation accuracy and the effectiveness of co-location.

• 出版日期2014
• 单位哈尔滨工程大学