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RFID (Radio Frequency Identification) positioning method based on means clustering random particle swarm optimization algorithm

A particle swarm algorithm and mean clustering technology, used in positioning, navigation calculation tools, measurement devices, etc., can solve problems such as affecting positioning efficiency and accuracy, incomplete noise processing, and large positioning errors.

Active Publication Date: 2019-03-08
HEFEI UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Among them, the signal acquisition in the VIRE algorithm is likely to contain noise, and the processing of the noise is not complete enough, resulting in a large positioning error. At the same time, there are multipath problems and redundant calculation problems caused by the complexity of the virtual reference tag positioning algorithm. Positioning Efficiency and Accuracy

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  • RFID (Radio Frequency Identification) positioning method based on means clustering random particle swarm optimization algorithm
  • RFID (Radio Frequency Identification) positioning method based on means clustering random particle swarm optimization algorithm
  • RFID (Radio Frequency Identification) positioning method based on means clustering random particle swarm optimization algorithm

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Embodiment Construction

[0079] see figure 1 , the RFID positioning method based on mean value clustering stochastic particle swarm algorithm in the present embodiment comprises the following steps:

[0080] Step 1: If figure 2 As shown in , place M reference tags, K readers, and a tag to be positioned randomly in the designated indoor area. The coordinates of each reference tag are known, and the RSSI of the tag to be positioned and each reference tag is obtained by the reader. Signal strength, because the signal strength obtained by different readers at different times is different, so it is taken as a function of nonlinear change: the RSSI signal strength of the reference tag ref obtained by the reader k at time t is recorded as the reference Label Signal Strength RSSI refk (t), record the RSSI signal strength of the tag to be positioned by the reader k at time t as the signal strength of the tag to be positioned RSSI tagk (t), where 1≤ref≤M, 1≤k≤K.

[0081] Step 2: Using the threshold wavelet...

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Abstract

The invention discloses an RFID (Radio Frequency Identification) positioning method based on a means clustering random particle swarm optimization algorithm, which comprises the steps of: placing reference tags, readers and a to-be-positioned tag in a specified indoor region, and by the readers, acquiring signal intensity of the reference tags and the to-be-positioned tag; carrying out signal processing on the signal intensity of the reference tags and the signal intensity of the to-be-positioned tag by adopting a threshold wavelet algorithm and eliminating noise; randomly generating initialized particles in a positioned region, using the initialized particles as virtual reference tags, and by a quadratic regression curve interpolation method, obtaining signal intensity of each particle; and carrying out clustering partitioning on all the initialized particles, calculating an optimal virtual reference tag position by an established means clustering random particle swarm optimization model, and according to the optimal virtual reference tag position, estimating a position of the to-be-positioned tag. The RFID positioning method can be widely applied to indoor positioning monitoringsystems for various warehousing freight transportation, and has the characteristics of high accuracy, high rate, high stability, low cost and the like.

Description

technical field [0001] The invention relates to an indoor positioning method based on radio frequency, more specifically an RFID positioning method based on mean value clustering random particle swarm algorithm, especially applied to the positioning of large-scale warehouse freight, and belongs to the technical field of monitoring and positioning. Background technique [0002] With the development of wireless local area network technology, especially the rise of Internet of Things technology, people have higher and higher requirements for location-based services, such as determining the location of goods in shopping malls when shopping, the safe positioning of children, and the security of luggage at the airport. for location tracking, etc. In the prior art, the global satellite positioning system is the most widely used for outdoor positioning; however, the indoor environment is often complicated, there are many obstacles, the signal blocking effect is extremely obvious, an...

Claims

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Application Information

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IPC IPC(8): G01C21/20G01S5/10
CPCG01C21/206G01S5/10
Inventor 肖本贤张旭黄俊杰江志政
Owner HEFEI UNIV OF TECH