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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Centralized and distributed multisensor integration with uncertainties in communication networks
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Centralized and distributed multisensor integration with uncertainties in communication networks

机译：通信网络中不确定性的集中式和分布式多传感器集成

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摘要

Algorithms in which each sensor is represented in a local coordinate system and the communication networks between sensors have uncertainties are considered. The algorithms are general and can be applied to various integration tasks. The effects of the communication network uncertainties are minimized in the local estimation and central fusion processes. In the centralized multisensor integration, the local measurements and local measurement models are transferred to the central coordinate system and the optimal integration is obtained at the central process. In contrast, the local measurements, together with the previous central estimate transmitted from the communication network, are locally processed in the distributed multisensor integration algorithm. Because the distributed algorithm uses the communication networks twice, more errors are introduced, so that when the uncertainties are large, the centralized algorithm is preferred. Although the algorithms are developed in the three-dimensional coordinate system, with straightforward extension they can be applied to N-dimensional coordinate systems.
机译：考虑了在局部坐标系中表示每个传感器并且传感器之间的通信网络具有不确定性的算法。该算法是通用的，可以应用于各种集成任务。在本地估计和中央融合过程中，将通信网络不确定性的影响最小化。在集中式多传感器集成中，将局部测量和局部测量模型转移到中心坐标系，并在中央过程中获得最佳集成。相反，在分布式多传感器集成算法中对本地测量值以及从通信网络发送的先前的中心估计值进行本地处理。由于分布式算法两次使用通信网络，因此引入了更多的错误，因此当不确定性较大时，首选集中式算法。尽管算法是在三维坐标系中开发的，但通过直接扩展，它们可以应用于N维坐标系。

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