Data fusion in decentralized sensor networks

By S. Grime, H. F. Durrant-Whyte. 1994

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Citations in the corpus

A survey of data fusion in smart city applications (2019, background): “Examples of O 1 can be found in [27], [42]–[44].”
A scheme for robust distributed sensor fusion based on average consensus (2005, background): “A further step would be trying to apply such diffusion schemes in distributed Kalman filter (or information filter); see [23] and the recent work [7].”
Distributed Kalman Filter with Embedded Consensus Filters (2005, background): “An in-depth comparison between the distributed Kalman filter introduced here and the existing decentralized sensor fusion algorithms both with and without fusion centers in [34], [28], [6], [11] is the subject of ongoing investigation.”
Decentralized Environmental Modeling by Mobile Sensor Networks (2008, background): “The utility of the information form for decentralized filtering has long been recognized [9], [16], [18], [40], [44], as the correction step of the filter involves simply summing independent computations on the measurements from the individual sensors.”
A Review of Data Fusion Techniques (2013, methodology): “Decentralized data fusion algorithms typically communicate information using the Fisher and Shannon measurements instead of the object’s state [8]; The main disadvantage of this architecture is the communication cost, which is 𝑂(𝑛 2 ) at each communication step, where 𝑛 is the number of nodes;…”
Consensus Filters for Sensor Networks and Distributed Sensor Fusion (2005, background): “Sensor networks have broad applications in surveillance & monitoring of an environment, collaborative processing of information, and gathering scientific data from spatially distributed sources for environmental modeling and protection [21], [ 8 ], [5], [10], [12], [2], [1], [3], [15], [16], [19], [”
Approaches to Multisensor Data Fusion in Target Tracking: A Survey (2006, background): “This is important as [188] had shown this to be impossible with a KF.”
Optimal linear estimation fusion .I. Unified fusion rules (2003, methodology): “If there is no fusion center, such as for the distributed sensor network structure considered in [ 15 ], each sensor can use the fusion rules presented here to obtain the best estimator based on its own observations and any information received from other sensors.”
Information fusion for wireless sensor networks: Methods, models, and classifications (2007, background): “For instance, Li et al. [2006] propose a source localization algorithm for a system equipped with asynchronous sensors wherein range data is collected (Collection step) and selected (Collation step).”