Indoor fusion positioning method based on multi-features

A positioning method and internal fusion technology, applied in positioning, measuring devices, instruments, etc., can solve the problems of inability to provide, difficult to take into account cost and accuracy, high positioning accuracy and stability, etc.

Active Publication Date: 2016-11-16
SUN YAT SEN UNIV +1
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Problems solved by technology

At present, the main problem of indoor positioning is that it is difficult to balance cost and accuracy at the same time, and many positioning methods require the deployment of additi

Method used

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  • Indoor fusion positioning method based on multi-features
  • Indoor fusion positioning method based on multi-features
  • Indoor fusion positioning method based on multi-features

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Embodiment

[0020] Such as figure 1 As shown, the multi-feature-based indoor fusion positioning method is divided into three major parts, namely Wi-Fi fingerprint probability calculation, inertial navigation calculation and particle filter fusion. The Wi-Fi fingerprint probability calculation uses the cosine similarity matching algorithm. The inertial navigation calculation is divided into three parts: step count calculation, step length calculation and walking direction estimation. The steps are calculated using the methods of walking detection, angular velocity filtering, center moving average, window peak detection, dynamic time warping, derivative analysis filtering and peak resurrection. The step length calculation uses the relationship model between step length and step frequency. The time-domain and frequency-domain analysis of the horizontal acceleration and the adjustment strategy based on the direction of gravity are given. Finally, in the particle filter fusion part, based on...

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Abstract

The invention discloses an indoor fusion positioning method based on multi-features. The whole process of the method is divided into three parts such as Wi-Fi fingerprint probability calculation, inertial navigation calculation and particle filtering fusion, wherein the Wi-Fi fingerprint probability calculation uses a cosine similarity matching algorithm, the inertial navigation calculation is divided into three parts such as step number calculation, step size calculation and walking direction estimation, the step number calculation uses methods such as walking detection, center moving equating, window wave peak detection, dynamic time regularization, derivative analysis filtering and wave peak resurrection, the step size calculation uses a step size and step frequency relationship model, the walking direction estimation uses the time and frequency zone analysis of a horizontal direction acceleration and strategy adjusting based on a gravity direction, and finally in the particle filtering fusion part, the hidden markov model constructed based on the inertial navigation and the Wi-Fi fingerprint probability uses the particle filtering method and combines with the map information to calculate the position probability so as to finally obtain the positioning result.

Description

technical field [0001] The invention relates to an indoor fusion positioning method based on multiple features. Background technique [0002] At this stage, indoor positioning technologies are very diverse, such as camera positioning, infrared positioning, magnetic field positioning, WIFI positioning, Bluetooth positioning, inertial navigation system positioning, ultrasonic positioning and so on. According to different hardware support, there are also different measurement methods. For example, in radio wave positioning, there are triangulation methods such as TOA, TDOA and AOA, as well as fingerprint matching measurement methods and so on. At present, the main problem of indoor positioning is that it is difficult to balance cost and accuracy at the same time, and many positioning methods require the deployment of additional positioning aids. However, Wi-Fi fingerprint positioning, as a common method for mobile terminal positioning, cannot provide high positioning accuracy...

Claims

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Application Information

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IPC IPC(8): G01C21/20G01C21/00G01C21/16G01S5/02
CPCG01C21/005G01C21/165G01C21/206G01S5/0257
Inventor 刘宁张韬陈沛尧牛群杨进参王作辉
Owner SUN YAT SEN UNIV
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