Research On Indoor Positioning Method Of Wireless Sensor Networks Based On IA-PSO Optimization

Wireless Sensor Networks(WSN)technology integrates embedded computing technology and wireless communication technology and other related technologies.It is an important foundation for the emerging Internet of Things.It is foreseeable that wireless sensor networks will have a profound impact in the near future.Change the way people live and produce.There are many researches on wireless sensor networks,but the research on node location technology has always been the focus,because the accuracy of node location information is very high in the process of sensor network data acquisition.If the information of the node location is not accurate enough,it will directly affect the data information to be studied in the next step.The main research work of this dissertation is:This dissertation first studies several classical positioning algorithms based on ranging and based on no ranging,and compares and analyzes their positioning performance.For the positioning error caused by the minimum hop count,the double communication radius is introduced to accurately estimate the hop count of the DV-Hop localization algorithm;for the positioning error caused by the average hop distance,multiple anchor nodes near the unknown node are introduced to correct the unknown node.Average hopping distance;combining two optimization algorithms at different stages into an improved positioning algorithm based on hop hopping optimization.The improved positioning algorithm has its own advantages.In the calculation stage of the unknown node coordinate position,this paper combines the particle swarm algorithm with the immune algorithm,and proposes the IA-PSO algorithm to optimize the above proposed algorithm.Finally,the traditional DV-Hop localization algorithm and three improved localization algorithms are simulated under the same conditions.The experimental results show that the improved three algorithms have better positioning accuracy and positioning stability than the original localization algorithm,and raised dramatically.At the same time,the IA-PSO-optimized algorithm has higher positioning accuracy and faster convergence than a single particle swarm optimization algorithm.