Three-dimensional wireless sensor network node self-locating method based on neural network

Abstract

The invention discloses a three-dimensional wireless sensor network node self-locating method based on a neural network. The three-dimensional wireless sensor network node self-locating method comprises the following steps that firstly initializing a wireless sensor network, secondly establishing a neural network, thirdly extracting training examples for the neural network, fourthly training the neural network through the obtained training examples, fifthly obtaining the actual distance from each unknown node to an anchor node which is not adjacent to the unknown node according to the well-trained neural network, and sixthly obtaining the three-dimensional coordinates of the known node. The obtaining method of the training examples is simple and has strong representative, and the well-trained neural network can better represent the main properties of a geometric structure of the three-dimensional wireless sensor network. The three-dimensional wireless sensor network node self-locating method solves the problem of overlarge estimation error of distance brought by the accumulation system of shortest jumping distances in the locating process of the three-dimensional wireless sensor, and effectively improves the locating precision.

Description

technical field [0001] The invention relates to the field of self-positioning of wireless sensor network nodes, in particular to self-positioning of nodes of wireless sensor networks in three-dimensional space, and a method for self-positioning of three-dimensional wireless sensor network nodes based on neural networks. Background technique [0002] With the development of wireless communication, sensors, micro-electromechanical systems, digital electronics and other technologies, the data-centric wireless sensor network (WSN) has become one of the research hotspots in the field of IT. Wireless sensor nodes have the functions of data collection, processing and communication, which can monitor, perceive and process various environmental information in the distribution area of ​​wireless sensor network in real time, and then transmit the information to the end users who need it. Wireless sensor networks have a wide range of applications in military security, environmental moni...

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Problems solved by technology

[0007] However, the above method does not consider the impact of the shortest hop distance on the positioning performance when the unknown node and the anchor node are not adjacent; it only roughly obtains the samples required for neural network training, and the representativeness of the samples is not strong, and the trained neural network cannot be better. It reflects the main properties of the geometric structure of wireless

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