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Distributed Estimation From Relative and Absolute Measurements

机译：相对和绝对测量的分布式估计

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摘要

This note defines the problem of least squares distributed estimation from relative and absolute measurements, by encoding the set of measurements in a weighted undirected graph. The role of its topology is studied by an electrical interpretation, which easily allows distinguishing between topologies that lead to “small” or “large” estimation errors. The least squares problem is solved by a distributed gradient algorithm: the computed solution is approximately optimal after a number of steps that does not depend on the size of the problem or on the graph-theoretic properties of its encoding. This fact indicates that only a limited cooperation between the sensors is necessary.
机译：本注释通过在加权无向图中对一组测量值进行编码，定义了根据相对和绝对测量值进行最小二乘分布估计的问题。通过电子解释研究其拓扑的作用，该解释可以轻松地区分导致“小”或“大”估计误差的拓扑。最小二乘问题是由分布式梯度算法解决的：在不依赖于问题的大小或其编码的图论特性的许多步骤之后，所计算的解近似为最佳。该事实表明，传感器之间仅需要有限的配合。

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