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Method for WLAN indoor positioning Radio Map updating based on information entropy

An indoor positioning and update method technology, applied in the field of information theory, can solve problems such as poor positioning accuracy, heavy update workload, and complex positioning

Active Publication Date: 2014-07-23
严格集团股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems of poor positioning accuracy, complex positioning and heavy updating workload in the existing WLAN indoor positioning Radio Map updating method, the present invention further provides a RadioMap updating method based on a Hidden Markov Model (HMM)

Method used

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  • Method for WLAN indoor positioning Radio Map updating based on information entropy
  • Method for WLAN indoor positioning Radio Map updating based on information entropy
  • Method for WLAN indoor positioning Radio Map updating based on information entropy

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Experimental program
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specific Embodiment approach 1

[0020] Embodiment 1: WLAN indoor positioning Radio Map update and positioning method based on information entropy. It includes the following steps:

[0021] Step 1: According to the relevant characteristics of radio propagation indoors and the frequency bands that APs can use, reasonably deploy APs to ensure that the signal strengths from at least two APs can be collected anywhere in the environment, and the signal power is greater than or equal to -95dBm;

[0022] Step 2: According to the indoor environment that needs to be positioned, select the appropriate coordinate origin to establish a two-dimensional rectangular coordinate system, set the reference points evenly and calibrate the coordinates of each reference point according to the rectangular coordinate system, and measure the distance from each AP at each reference point Radiation signal strength and save the two-dimensional coordinates of the reference point and the measured AP signal strength in the Radio Map;

[0...

specific Embodiment approach 2

[0027] Specific embodiment two: In step 2 of this embodiment, "measure the radiation signal strength from each AP at each reference point and save the two-dimensional coordinates of the reference point and the measured AP signal strength in the Radio Map" The specific operation steps are:

[0028] At each reference point in the area to be updated, use the signal receiver to collect and record the received signal strength RSS value from each AP n times and record the two-dimensional coordinates of the reference point, forming N×n×(M+2) Matrix, where N is the number of reference points in the area to be updated, n is the number of signal acquisitions at each reference point, M in M+2 represents the number of APs in the environment, 2 represents two-dimensional coordinates, and is saved in Radio Map middle.

[0029] Other implementation manners are the same as the specific implementation manner 1.

specific Embodiment approach 3

[0030] Specific implementation mode three: the specific operation steps of "selecting r APs with larger information entropy gains" in step 3 of this implementation mode are as follows:

[0031] Step 3.1: Calculate the information entropy gain (Information Gain, IG) of each AP in the area to be updated, according to the formula (1), where H(l) represents the information entropy of the user location, as shown in the formula (2), where p(l g ) means that when the user is at position l g , the probability at g={1,2,…N}, for the convenience of use, it is considered that the probability of the user at each reference point is equal to Thus formula (2) is shown in formula (4), when the test point is obtained from the ith AP (AP i When the signal strength RSS value of ) is known, the uncertainty of the actual position of the test point, that is, the conditional entropy value H(l|AP i ) is calculated as formula (4), where p(l g |AP i =v e ) stands for AP i =v e Under the condit...

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Abstract

The invention provides a method for WLAN indoor positioning Radio Map updating based on information entropy and relates to a WLAN indoor positioning method. The method solves the problem that an existing WLAN indoor positioning Radio Map updating method is poor in positioning accuracy, has complexity in positioning and is large in updating workload. AP signal strength RSS values measured in every reference point are stored in a Radio Map, APs with information entropy large are selected, mutual information entropy between every two APs is calculated; after the APs with information entropy large are selected, a Hidden Markov model is utilized to update the Radio Map at an off-line stage, a KNN algorithm is used to respectively compare positioning accuracy of the Radio Map at the off-line stage and the updated Radio Map with RSS vectors measured at an on-line stage, and the updated Radio Map is favorable for improving positioning accuracy compared with the Radio Map prior to updating. The method is suitable for WLAN indoor positioning.

Description

technical field [0001] The invention relates to a Radio Map update method for WLAN indoor positioning in the field of information theory, in particular to a WLAN indoor positioning method. Background technique [0002] With the popularization of smart phones, location-based services are getting more and more attention. Today's satellite positioning only solves the problem of outdoor positioning, and indoor positioning has not yet been unified. The proposal of the IEEE802.11 standard makes the deployment of Wireless Local Area Networks (WLANs) more and more widespread. The indoor positioning method based on WLAN has attracted extensive attention because of its convenient deployment and no need to add other hardware devices. [0003] The WLAN indoor positioning technology estimates the location of the mobile device by measuring the received signal strength (RSS) from the access point AP (Access Point). Usually the positioning system is divided into two steps, that is, the o...

Claims

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Application Information

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IPC IPC(8): H04W64/00H04W84/12
Inventor 马琳邹贵张中兆莫云夏颖徐玉滨
Owner 严格集团股份有限公司
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