Deployment method of large-scale RFID readers in three-dimensional space

Abstract

The present invention proposes a large-scale RFID reader deployment algorithm in three-dimensional space, which is characterized in that the algorithm adopts a quantitative method to convert the reader-writer model and the area model to be covered in three-dimensional space into a three-dimensional matrix, and then Using matrix theory, the reader deployment problem is transformed into a three-dimensional matrix deployment problem. At the same time, in view of the difference in the propagation direction of the reader antenna, a method of using the rotation matrix to construct the three-dimensional coverage model matrix group of the reader is proposed, so as to map the placement of the reader antenna. And the method of calculating the deployment performance index: coverage rate and overlap rate in the deployment strategy is given. Finally, for the deployment of RFID readers, this algorithm proposes an improved strategy of PSO algorithm based on elimination rules. This strategy adds reader out-of-bounds detection and elimination mechanism, and improves the standard PSO algorithm.

Description

technical field [0001] The invention relates to a deployment method of large-scale RFID readers in three-dimensional space. Firstly, the method carries out three-dimensional modeling of the RFID reader, transforms the NP-hard problem of RFID reader deployment in three-dimensional space into a three-dimensional matrix deployment problem, and establishes A three-dimensional matrix reader model is proposed, which is simple to implement in deployment simulation and has low computational complexity. At the same time, an improved particle swarm optimization algorithm based on elimination rules is proposed, which adds the out-of-bounds detection of reader coverage and For the discarding of bad particles in the population, compared with the standard particle swarm optimization algorithm, this algorithm can not only detect invalid readers deployed outside the coverage area and bring them back into the target area, but also prevent the population from falling into a local optimal soluti...

AI Technical Summary

Problems solved by technology

[0009] Standard PSO is a random search algorithm. Its advantage is that the algorithm can quickly converge in the initial stage of iteration, but in the later stage of algorithm iteration, all particles are close to the optimal particle in the group, and the position difference between particles Gradually decreases, and the speed of the particles gradually tends to zero from the initial speed. At this time, the particles lose the ability to explore new spaces due to lack of activity, and the algorithm is easily trapped in the local extremum

Moreover, this phenomenon cannot be significantly improved with the increase of the number of iterations of the algorithm.

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