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Indoor positioning method fusing multi-source data

A multi-source data, indoor positioning technology, applied in the field of indoor positioning that integrates multi-source data, can solve the problems of poor accuracy of single-mode positioning methods, and achieve the effect of improving positioning accuracy and robustness

Inactive Publication Date: 2019-05-17
深圳市交投科技有限公司
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Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of poor accuracy based on single-mode positioning methods, and provid

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  • Indoor positioning method fusing multi-source data
  • Indoor positioning method fusing multi-source data
  • Indoor positioning method fusing multi-source data

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[0019] The present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

[0020] Behavior recognition refers to judging the behavior attributes of pedestrians through the data collected by multiple sensors of smartphones, so the problem of behavior recognition is a classification problem. The main steps of behavior recognition are figure 1 shown, including data preprocessing, data segmentation, feature extraction, feature dimensionality reduction, and classification.

[0021] Data preprocessing is mainly used to filter out noise signals in sensor data, such as high-frequency noise in acceleration data, which can be implemented by using a low-pass filter. Data segmentation mainly extracts effective information from continuous time series data for behavior recognition. Feature extraction is used to extract categorical features from segmented data to form feature vectors, which are used to distinguish behavior...

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Abstract

The invention discloses an indoor positioning method fusing multi-source data, comprising the following steps: A) modeling the indoor movement process of pedestrians into a hidden Markov model, fusingthe multi-source data by using the hidden Markov model, and taking the observation value of the hidden Markov model as a single-mode perception result; B) modeling the indoor map into a graph structure to obtain a node transition probability; and C) calculating the position of the user through a Viterbi algorithm so as to realize indoor positioning. The indoor positioning method based on multi-source data fusion is adopted, and on the basis of behavior recognition, WiFi positioning and pedestrian dead reckoning, multi-source perception data are fused through a hidden Markov model, so that thepositioning precision and robustness are improved.

Description

technical field [0001] The invention belongs to the technical field of wireless indoor positioning, and in particular relates to an indoor positioning method integrating multi-source data. Background technique [0002] With the rapid development and popularization of mobile Internet and intelligent mobile terminal technology represented by smart phones, mobile users have increasingly strong demand for location services, which brings huge opportunities for the application of location-based services (Location Based Service, LBS). with challenges. In people's daily life, pedestrian navigation is one of the most commonly used LBS applications. Positioning and navigation through smart mobile terminals such as smartphones and tablets have almost become an indispensable way of life for people. In pedestrian navigation systems, location information is one of the key factors. At present, the outdoor pedestrian navigation system has basically met people's travel needs, and its locat...

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Application Information

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IPC IPC(8): H04W64/00G06K9/62
Inventor 胡斌邹亮徐贵亮杨健刘军建杜志明
Owner 深圳市交投科技有限公司
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