Indoor positioning method based on hidden Markov model

An indoor positioning and model technology, applied in the field of wireless networks, can solve problems such as difficult to collect RSSI data, achieve the effects of reducing errors, high positioning accuracy and stability, and improving positioning accuracy and stability

Active Publication Date: 2015-03-25
少年强(厦门)体育产业有限公司
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Problems solved by technology

However, this method of multiple measurements can only be applied to targets with weak moving characteristics. When the moving characteristics of the target to be located are strong, it is often difficult for the system to collect multiple RSSI data at the same position.

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  • Indoor positioning method based on hidden Markov model
  • Indoor positioning method based on hidden Markov model
  • Indoor positioning method based on hidden Markov model

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Embodiment Construction

[0032] The present invention defines the positioning model based on the hidden Markov model, that is, the hidden Markov positioning model is a five-tuple HMLM={n, m, П, A, B}, wherein, n is the number of reference positions, m is the number of beacon base stations, Π=π i , i =1,...,n, π i represents the initial state i The probability of , A is the position transition matrix, B is the confusion matrix. The indoor positioning method based on the hidden Markov model of the present invention includes an offline stage and a real-time positioning stage.

[0033] The offline phase consists of the following steps:

[0034] Step 101: Setting beacon base stations and reference positions according to the positioning area.

[0035] Step 102: Establish an undirected connected graph of the reference location, and establish a location transition matrix according to the undirected connected graph of the reference location. Among them, the construction method of the position transfer ma...

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Abstract

The invention relates to an indoor positioning method based on a hidden Markov model. According to the indoor positioning method, an RSSI fingerprint feature is utilized for positioning, and an offline stage and a real-time positioning stage are included. The offline stage comprises the steps that beacon base stations and reference positions are set; an undirected connected graph of the reference positions is set up, and a position transfer matrix is set according to the undirected connected graph; the RSSI feature values of the beacon base stations are collected at all the reference positions, and an RSSI fingerprint database of a positioned area is set up; the confusion matrix of the reference positions and RSSI fingerprints is set up through a bayes method, and a hidden Markov positioning model is set up. The real-time positioning stage comprises the steps that mobile equipment collects the real-time RSSI feature values and sends the real-time RSSI feature values to a positioning server; the positioning server calculates a track sequence with the maximum continuous motion possibility, and the last position of the track sequence is adopted as a positioning result. According to the method, errors caused by RSSI fluctuation in the continuous motion process to the positioning result can be effectively reduced, and the precision and stability of indoor wireless positioning are improved.

Description

technical field [0001] The invention relates to the technical field of wireless networks, in particular to an indoor positioning method based on a hidden Markov model, which can be applied to the positioning of moving objects such as people or vehicles indoors. Background technique [0002] Because it can adapt to complex indoor multipath effects, the non-ranging based RSSI fingerprint positioning method has been widely used in various indoor positioning systems. In an indoor environment, since the propagation of wireless signals is easily affected by temperature, humidity and people's movement, the measured value of RSSI fluctuates greatly. In order to improve the stability and precision of measurement, many positioning algorithms based on RSSI often adopt the method of averaging or weighting multiple acquisitions. However, this method of multiple measurements can only be applied to targets with weak moving characteristics. When the moving characteristics of the target to ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W64/00
CPCH04W64/00H04W64/006
Inventor 叶阿勇绍剑飞陈秋玲郑永星李亚成
Owner 少年强(厦门)体育产业有限公司
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