Wireless positioning method and system based on depth learning

A wireless positioning system and deep learning technology, applied in the field of wireless positioning methods and systems based on deep learning, can solve the problem of low positioning accuracy and achieve the effect of improving accuracy

Inactive Publication Date: 2017-08-18
PHICOMM (SHANGHAI) CO LTD
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  • Abstract
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Problems solved by technology

[0009] The technical problem to be solved by the present invention is to provide a wireless position

Method used

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  • Wireless positioning method and system based on depth learning
  • Wireless positioning method and system based on depth learning
  • Wireless positioning method and system based on depth learning

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Embodiment Construction

[0087] The following are specific embodiments of the present invention and in conjunction with the accompanying drawings, the technical solutions of the present invention are further described, but the present invention is not limited to these embodiments.

[0088] The embodiment of the present invention provides a wireless positioning method based on deep learning, such as figure 1 shown, including steps:

[0089] S11: collect the wireless signal strength received by all sampling points;

[0090] S12: Using a deep learning algorithm to input the collected wireless signal strength and coordinates into a deep learning neural network to generate a weighted deep learning neural network;

[0091] S13: Collect the wireless signal strength of the user's location and input it into the weighted deep learning neural network to determine the user's location.

[0092] The concept of deep learning originated from the study of artificial neural networks. A multi-layer perceptron with mu...

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Abstract

The invention discloses a wireless positioning method and system based on depth learning and aims to solve a problem of non-high indoor positioning precision. The method comprises steps that S1, wireless signal intensities received by all sampling points are acquired; S2, a depth learning algorithm is utilized to input the acquired wireless signal intensities and coordinates to a depth learning neural network to generate a depth learning neural network with a weight; and S3, wireless signal intensities of users are acquired and are inputted to the depth learning neural network with the weight to determine the positions of the users. The method is advantaged in that indoor positioning precision can be improved, and an over-fitting problem in a full connection layer of the neural network can be avoided.

Description

technical field [0001] The present invention relates to the field of wireless indoor positioning, in particular to a deep learning-based wireless positioning method and system. Background technique [0002] With the rapid development and popularization of mobile computing devices, the demand for various location-based services in indoor environments is increasingly urgent. Due to the existing satellite positioning systems, such as the US Global Positioning System (GPS) and China's Beidou satellite positioning system, in indoor environments or up to urban areas with dense buildings, satellite positioning signals are blocked by buildings, making it difficult to effectively locate. At present, indoor positioning generally uses infrared, ultrasonic, radio frequency and other sensing signals. Among them, the positioning technology based on infrared and ultrasonic has higher accuracy, but it needs to use special hardware facilities, and the signal needs to be transmitted in line o...

Claims

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Application Information

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IPC IPC(8): G01S11/06G06N3/08H04W64/00
CPCG01S11/06G06N3/084H04W64/00
Inventor 乐毅
Owner PHICOMM (SHANGHAI) CO LTD
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