论文信息 - On Distributed and Decentralized Estimation

On Distributed and Decentralized Estimation

This paper presents the information form of the decentralized and distributed Kalman filter. Use of the Information filter allows straightforward fusion of new observations. The minimal communication of information between reduced order, globally optimal fusion centers is explained using a transformation diagram.

T. M. Berg | H. F. Durrant-Whyte

[1] D. Catlin. Estimation, Control, and the Discrete Kalman Filter , 1988 .

[2] A. Willsky,et al. Combining and updating of local estimates and regional maps along sets of one-dimensional tracks , 1982 .

[3] Ali T. Alouani,et al. Nonlinear data fusion , 1989, Proceedings of the 28th IEEE Conference on Decision and Control,.

[4] Sumit Roy,et al. Decentralized structures for parallel Kalman filtering , 1988 .

[5] R. E. Kalman,et al. A New Approach to Linear Filtering and Prediction Problems , 2002 .

[6] Huosheng Hu,et al. Toward a fully decentralized architecture for multi-sensor data fusion , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[7] S. Grime,et al. Communication in Decentralized Data-Fusion Systems , 1992 .

[8] T. M. Berg,et al. Model Distribution in Decentralized Multi-Sensor Data Fusion , 1991, 1991 American Control Conference.

[9] Jason Speyer,et al. Computation and transmission requirements for a decentralized linear-quadratic-Gaussian control problem , 1978, 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes.

[10] Ali T. Alouani,et al. Distributed estimation: constraints on the choice of the local models , 1988 .