An improved DV-Hop localization method based on hybrid firefly particle swarm optimization

By using the hybrid firefly particle swarm optimization algorithm in the wireless sensor network, weighted secondary correction and error correction are performed, the problem of the DV-Hop positioning algorithm degradation in the node randomly distributed network is solved, and higher positioning accuracy and stability are achieved.

CN114745657BActive Publication Date: 2025-03-28NANJING UNIV OF POSTS & TELECOMM
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Patent Information

Application Number
CN202210169624.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-02-23
Publication Date
2025-03-28
Estimated Expiration
2042-02-23

AI Technical Summary

Technical Problem

In wireless sensor networks, the DV-Hop positioning algorithm decreases positioning accuracy in a randomly distributed network of nodes, and traditional optimization algorithms are prone to fall into local optimal solutions.

Method used

The hybrid firefly particle swarm optimization algorithm is used to correct the average jump distance between anchor nodes by weighted quadratic correction and the single jump distance correction using error factors to finally optimize the coordinates of unknown nodes.

Benefits of technology

It improves node positioning accuracy and stability, avoids the defect of particle optimal solution to local optimality, and adapts to various random wireless sensor network structures.

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Abstract

An improved hybrid firefly particle swarm optimization DV-Hop positioning method not only corrects the average hop distance between anchor nodes by weighted quadratic correction, but also uses the error factor for further correction, and uses the hybrid firefly particle swarm algorithm to optimize the coordinates of unknown nodes. By using the improved firefly and particle swarm algorithms under different applicable conditions, not only the global search speed of particles is guaranteed to be fast, but also the defect of the particle optimal solution falling into the local optimum is avoided. Compared with the current traditional DV-Hop position calculation and optimization methods, the present invention effectively improves the positioning accuracy and stability of nodes.
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