An overview of non-centralized Kalman filters

The usage of wireless sensor networks (WSNs) for state-estimation has recently gained increasing attention due to its cost effectiveness and feasibility. One of the major challenges of state-estimation via WSNs is the distribution of the centralized state-estimator among the nodes in the network. Significant emphasis has been on developing non-centralized state-estimators considering communication, processing-demand and estimation-error. This survey paper presents different methodologies to obtain non-centralized state-estimators and focuses on the estimation algorithms and their implementation. The temperature distribution of a bar is used as a benchmark to assess the non-centralized state-estimators in terms of estimation-error and communication requirements.

[1]  Shu-li Sun,et al.  Multi-sensor optimal information fusion Kalman filters with applications , 2004 .

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

[3]  A. Rantzer,et al.  Distributed Kalman Filtering Using Weighted Averaging , 2006 .

[4]  Roy S. Smith,et al.  Closed-Loop Dynamics of Cooperative Vehicle Formations With Parallel Estimators and Communication , 2007, IEEE Transactions on Automatic Control.

[5]  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.

[6]  Jeffrey K. Uhlmann,et al.  A non-divergent estimation algorithm in the presence of unknown correlations , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[7]  Celso Pascoli Bottura,et al.  AN APPROACH FOR DISTRIBUTED KALMAN FILTERING , 2001 .

[8]  Stephen P. Boyd,et al.  A scheme for robust distributed sensor fusion based on average consensus , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

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

[10]  Sumit Roy,et al.  Square root parallel Kalman filtering using reduced-order local filters , 1991 .

[11]  S. C. Felter An overview of decentralized Kalman filter techniques , 1990, IEEE Technical Conference on Southern Tier.

[12]  J. Speyer Computation and transmission requirements for a decentralized linear-quadratic-Gaussian control problem , 1979 .

[13]  M. F. Hassan,et al.  A decentralized computational algorithm for the global Kalman filter , 1978 .

[14]  R. Olfati-Saber,et al.  Distributed Kalman Filter with Embedded Consensus Filters , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[15]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[16]  Subhasish Subhasish,et al.  Decentralized linear estimation in correlated measurement noise , 1991 .

[17]  T. Başar,et al.  A New Approach to Linear Filtering and Prediction Problems , 2001 .

[18]  Hugh F. Durrant-Whyte,et al.  Fully Decentralized Estimation and Control for a Modular Wheeled Mobile Robot , 2000, Int. J. Robotics Res..

[19]  José M. F. Moura,et al.  Distributed Kalman Filters in Sensor Networks: Bipartite Fusion Graphs , 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.

[20]  Reza Olfati-Saber,et al.  Distributed Kalman filtering for sensor networks , 2007, 2007 46th IEEE Conference on Decision and Control.