Inertial navigation indoor positioning method based on BP neural network

A BP neural network, indoor positioning technology, applied in the field of indoor positioning, can solve the problems of low acceleration accuracy, rapid accumulation of inertial navigation positioning errors, etc., to achieve the effect of improving accuracy, improving positioning accuracy, and reducing measurement noise

Active Publication Date: 2019-04-05
YANSHAN UNIV
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Problems solved by technology

The currently used strapdown inertial navigation system uses acceleration data integration to obtain the step length. Sin...

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  • Inertial navigation indoor positioning method based on BP neural network
  • Inertial navigation indoor positioning method based on BP neural network
  • Inertial navigation indoor positioning method based on BP neural network

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Embodiment Construction

[0022] In order to make the purpose, method and advantages of the embodiments of the present invention more clear, the BP neural network-based inertial navigation indoor positioning method of the present invention will be further described below in conjunction with the accompanying drawings.

[0023] The present invention is described by taking a positioning person wearing an ankle wearable device and walking indoors as a specific example, using the wearable device's internal three-axis acceleration sensor, three-axis angular velocity sensor and three-axis magnetometer to record the data of the person's walking for indoor positioning. Such as figure 1 As shown, the inertial navigation indoor positioning method based on BP neural network of the present invention comprises motion data acquisition and preprocessing stage, off-line training stage and real-time positioning stage:

[0024] 1. Data acquisition and preprocessing stage, including the following specific steps:

[0025]...

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Abstract

The present invention discloses an inertial navigation indoor positioning method based on a BP neural network, including a motion data collection and preprocessing stage, an offline training stage, and a real-time positioning stage. Data collection is collecting movement data of two ankles, a stature, and a step size of a person by wearable devices on left and right ankles. Data preprocessing is using multi-sensor information fusion processing to obtain 7 pieces of neural network input data: variances of attitude angles of left and right legs theta1 and theta2, an acceleration average of the ankles, a variance, foot step duration of left and right feet time1 and time2, and a stature. The offline training stage includes: establishing a neural network step size estimation model; and inputting 7 pieces of input data and the step data to the neural network for training. The real-time positioning phase includes: performing step recognition within the wearable device on the right ankle, predicating a step size in real time, and implementing real-time positioning by using dead reckoning by using the step size and a direction angle. In the present invention, accuracy and real-time capability of indoor positioning are improved, and reliability is improved.

Description

technical field [0001] The invention relates to the field of indoor positioning, in particular to a BP neural network-based inertial navigation indoor positioning method. Background technique [0002] Existing indoor positioning technology solutions mainly include Wi-Fi positioning technology, infrared positioning technology, ultrasonic positioning technology, visible light positioning technology, UWB technology, ZigBee technology, radio frequency tag identification technology, and computer vision positioning technology. Because these technologies need to build equipment for auxiliary positioning, the higher the positioning accuracy, the more the number of auxiliary equipment is required, so these technologies are not universally applicable and fast. Wi-Fi positioning technology needs to estimate the location of the receiver by setting up a Wi-Fi network indoors. Visible light positioning technology needs to clarify the position of the visible light source in advance. If th...

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Application Information

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IPC IPC(8): G01C21/20G01C21/16
CPCG01C21/16G01C21/206
Inventor 童凯谢正威刘刚
Owner YANSHAN UNIV
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