Fuselage Indoor Fingerprint Localization Method Based on Improved Particle Swarm Optimization Algorithm
Ground testing for aircraft structural strength is a critical part of aircraft manufacturing.It is of great significance to safeguard the safety of personnel,enhance the performance,and reduce the cost.In order to improve the testing efficiency and obtain a higher positioning accuracy in indoor testing environment,this paper integrates the dual variational particle swarm optimization(DMPSO)algorithm into indoor wireless positioning,proposes an indoor fingerprint positioning method for aircraft fuselage structure strength test based on improved particle swarm optimization algorithm,and verifies its validity through experiments.The results show that compared with the traditional particle swarm optimization(PSO)algorithm and the maximum likelihood estimation(MLE)algorithm,the DMPSO proposed in this paper performs well in terms of average localization error(0.4341m),which is significantly better than that of the PSO of 0.7263m and MLE of 0.8089m.Therefore,the DMPSO method has higher localization accuracy and stability.The research of this paper not only provides a new approach for aircraft structural strength testing,but also provides an effective solution to improve the positioning accuracy of indoor wireless positioning.
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