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Pedestrian location method in indoor WLAN environment

A positioning method and pedestrian technology, applied in the field of computer programs, can solve problems such as the reduction of pedestrian movement positioning accuracy, and achieve the effects of good environmental adaptability, low sensitivity and high positioning accuracy

Inactive Publication Date: 2017-04-26
COMMUNICATION UNIVERSITY OF CHINA
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AI Technical Summary

Problems solved by technology

[0019] Aiming at the problem of reduced accuracy of pedestrian movement positioning in indoor WLAN environment, a hidden Markov model based on pedestrian movement positioning is proposed, using fuzzy thinking, using the reconstructed radio map and the planned path to estimate by fuzzy matching of RSSI change indicators Hidden Markov model transfer matrix, and finally use the hidden Markov transfer matrix and the RSSI change index obtained during actual positioning to estimate the user position, and realize the positioning of pedestrians in the process of moving

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  • Pedestrian location method in indoor WLAN environment
  • Pedestrian location method in indoor WLAN environment
  • Pedestrian location method in indoor WLAN environment

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Embodiment 1

[0052] Embodiment 1: as figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 as shown,

[0053] A pedestrian positioning method in an indoor WLAN environment. The WLAN positioning technology includes positioning technologies based on RSSI, angle of arrival (AOA for short) and time of arrival (TOA for short).

[0054] The positioning technology based on AOA and TOA requires additional special hardware equipment, and there is a large error in the measurement accuracy, so it is greatly limited in research and application.

[0055] The RSSI-based WLAN positioning technology of this application does not require additional special equipment, and the hardware cost is much lower than that of AOA and TOA positioning technologies.

[0056] RSSI-based positioning technology can be divided into two types of positioning methods according to the positioning principle: location fingerprint method and propagation model method. The difference between these two positioning methods is ...

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Abstract

The present invention provides a pedestrian location method in an indoor WLAN environment. The pedestrian location method in the indoor WLAN environment takes the Hidden Markov Model of the pedestrian mobile location as the basis, utilizes the fuzzy thinking, employs the reconstructed radio map and a planning path to estimate a Hidden Markov Model transfer matrix through the RSSI changing index fuzzy matching and finally employs the Hidden Markov Model transfer matrix to match the RSSI changing index obtained at the real location to estimate the user position so as to realize the location in the pedestrian mobile process. The fuzzy matching algorithm estimates the pedestrian position through the proportional relation of the wireless network signal fading and the distance, the fuzzy matching algorithm can be also individually used for pedestrian mobile location, and because of the iterative computations character, big location errors are likely to be introduced so as to introduce the Hidden Markov Model in the present invention. The pedestrian location method in the indoor WLAN environment can greatly improve the location precision when the pedestrian is moved in the indoor environment and has good environment adaptability and anti-interference performance.

Description

technical field [0001] The invention relates to a pedestrian positioning method in an indoor WLAN environment, and belongs to the technical field of computer programs. Background technique [0002] At present, in the indoor WLAN environment, the fingerprint positioning algorithm is mainly used to estimate the user location. The principle of the location fingerprint positioning algorithm is as follows: the received signal strength at different physical locations has complex, unique and distinguishable characteristics. According to this feature, a mapping relationship database (radio map) between physical location and RSSI value can be constructed. When the RSSI value of the user's location to be measured is obtained, the physical location corresponding to the RSSI value can be estimated theoretically. [0003] It can be seen from the principle that the key to the position fingerprint positioning algorithm is to be able to accurately measure the RSSI value when establishing a...

Claims

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Application Information

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IPC IPC(8): G01S5/02
CPCG01S5/02
Inventor 倪业鹏刘剑波刘杉
Owner COMMUNICATION UNIVERSITY OF CHINA
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