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Linear regression algorithm-based WLAN indoor positioning multi-user RSS (Received Signal Strength) fusion method

A linear regression and indoor positioning technology, applied in positioning, radio wave measurement systems, measuring devices, etc., can solve problems such as large positioning errors, achieve the effect of improving accuracy and improving positioning accuracy

Active Publication Date: 2016-06-08
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] The present invention aims to provide a WLAN indoor positioning multi-user RSS based on a linear regression algorithm for the purpose of the RSS data collected by users using different mobile terminals during the RadioMap establishment process and the online positioning phase. fusion method

Method used

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  • Linear regression algorithm-based WLAN indoor positioning multi-user RSS (Received Signal Strength) fusion method
  • Linear regression algorithm-based WLAN indoor positioning multi-user RSS (Received Signal Strength) fusion method
  • Linear regression algorithm-based WLAN indoor positioning multi-user RSS (Received Signal Strength) fusion method

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specific Embodiment approach 1

[0051] The specific embodiment one, WLAN indoor positioning multi-user RSS fusion method based on linear regression algorithm, it is realized by the following steps:

[0052] Step 1. In the offline RadioMap establishment phase, the smart mobile terminal perceives the surrounding environment in the background without affecting the normal use of the user, and uploads the perceived RSS value, terminal brand and other information to the server;

[0053] Step 2. The server selects a terminal of a certain brand as the basic terminal device, and performs linear regression processing on the RSS data collected by other terminals and the RSS value collected by the basic terminal device at several reference points, and obtains the RSS value after linear regression and the RSS value of different terminals. The linear regression coefficient between;

[0054] Step 3, use the obtained linear regression coefficients to perform linear regression processing on the RSS values ​​collected by diff...

specific Embodiment approach 2

[0058] Embodiment 2. This embodiment is a further limitation of the linear regression algorithm-based WLAN indoor positioning multi-user RSS fusion method described in Embodiment 1. The offline stage RadioMap establishment and analysis process includes the following steps:

[0059] 1. At each reference point in the area to be positioned, use different brands of mobile terminals 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 to form 4 N i ×n×(M+2), i=1,2,3,4 matrix, where N i The number of reference points for collecting RSS values ​​for a certain brand of terminal, i=1, 2, 3, and 4 represent Huawei, Xiaomi, Samsung, and Nexus terminals respectively, is the total number of reference points in the area to be located, n is the number of signal acquisitions at each reference point, M in M+2 represents the number of APs in the environment, and 2 represents the two-dimensional coord...

specific Embodiment approach 3

[0069] Embodiment 3: In the online positioning stage, the server performs linear regression processing on the RSS value collected by the user's mobile terminal to calculate the user's position coordinates, and calculates the error between the two-dimensional coordinates and the actual position. It consists of the following steps:

[0070] 1), such as Figure 4 As shown, the user selects the brand of his mobile terminal in the positioning software or the server independently identifies the brand of the user's mobile user terminal, so as to obtain the linear regression coefficient in RadioMap, and use the linear regression coefficient to perform linear regression processing on the RSS value measured by the mobile terminal After obtaining the RSS value after processing, the calculation formula is as shown in formula (1) in the second specific embodiment;

[0071] 2) Average the n times of RSS value vectors measured at each reference point in the RadioMap to obtain a 1×(M+2) vect...

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Abstract

The invention relates to a WLAN indoor positioning multi-user RSS (Received Signal Strength) fusion method, in particular, a linear regression algorithm-based WLAN indoor positioning multi-user RSS fusion method. The objective of the invention is to solve the problem of large positioning errors caused by large difference of RSS data acquired by users through using different mobile terminals in a radio map building process and an online positioning stage. According to the method of the invention, in an off-line stage, linear regression processing is performed on RSS values acquired by the different mobile terminals, and at the same time, the linear regression coefficients of the different mobile terminals and a base mobile terminal are stored; in an online positioning stage, a system obtains the brands of the mobile terminals of the users, and reads the linear regression coefficients from a radio map so as to perform linear regression processing on the RSS values acquired by the mobile terminals; and therefore, the differences between the RSS values which are acquired online and the RSS values in the radio map caused by the differences of devices can be eliminated, and online positioning accuracy can be improved.

Description

technical field [0001] The invention relates to a multi-user RSS fusion method for WLAN indoor positioning. Background technique [0002] With the deployment of Wireless Local Area Networks (WLAN) more and more widely and the popularity of smart phones, WLAN indoor positioning technology based on received signal strength RSS (Received Signal Strength) has attracted widespread attention because of its easy deployment and no need to add other hardware devices. [0003] The WLAN indoor positioning technology estimates the position of the mobile device by measuring the received signal strength RSS from the access point AP (AccessPoint). The WLAN positioning system consists of two parts, that is, the off-line RadioMap establishment stage and the on-line location estimation stage. The construction of RadioMap in the offline phase is the most important thing to ensure high-precision indoor positioning. RadioMap is composed of signal strength value vectors received by each referenc...

Claims

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Application Information

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IPC IPC(8): G01S5/02
CPCG01S5/021G01S5/0284
Inventor 徐玉滨张立晔马琳张文彬
Owner 严格集团股份有限公司
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