DV-Hop positioning algorithm based on sine and cosine optimization and hop optimization

Abstract

The invention relates to a DV-Hop positioning algorithm based on sine and cosine optimization and hop optimization, and belongs to the field of wireless sensor network node positioning. The method comprises the following steps: firstly, defining a concept of an optimal anchor node, selecting an anchor node with the minimum average hop distance in all anchor nodes around each unknown node as the optimal anchor node, then selecting any one of the rest anchor nodes and the unknown nodes to form a triangle, and taking an edge from the optimal anchor node to the unknown nodes as an optimal edge in the triangle; secondly, calculating the distances from other anchor nodes to the unknown node by using the cosine theorem to achieve the purpose of optimizing the hop distance; and finally, improving the least square method by using a sine and cosine optimization algorithm (SCA), and searching the optimal position of an unknown node by using the volatility of a sine and cosine function. According to the method, the positioning precision can be improved while the positioning cost is reduced, and the application range is widened.

Description

technical field [0001] The invention relates to a DV-Hop positioning algorithm based on sine-cosine optimization and segment-hopping optimization, and belongs to the field of wireless sensor network node positioning. Background technique [0002] The non-present sensor network realizes the functions of data collection, processing and transmission, and is widely used in various interdisciplinary fields such as forest fire early warning, dynamic tracking, and environmental monitoring. However, in the monitoring process, it is not only necessary to extract various monitoring data, but also to locate the target node in real time after analyzing the data, so as to realize the significance of monitoring. [0003] Although the traditional DV-Hop positioning method is a non-ranging node positioning method, the positioning cost is low, but there are large errors in the process of calculating the minimum hop value between nodes and the average hop moment of anchor nodes, resulting in ...

AI Technical Summary

Problems solved by technology

However, in the actual environment, related problems such as uneven node deployment and complex propagation environment will exist at any time, so higher requirements are put forward for the performance of the positioning algorithm to ensure that the positioning method can adapt to the actual application scenario

[0004] The sine-cosine optimization algorithm belongs to the swarm intelligence algorithm. It uses the principle of iterative optimization to optimize the target. It has strong global search ability, but has the disadvantage of weak local error search ability.

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