Indoor fusion positioning method based on improved PDR algorithm

A positioning method and internal fusion technology, which can be applied to services based on location information and services based on specific environments. It can solve problems such as unstable Wi-Fi fingerprint positioning results, and achieve the effect of maintaining stability and improving accuracy.

Pending Publication Date: 2021-04-09
WUHAN UNIV OF SCI & TECH
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However, due to the volatility of RSSI, the resu

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  • Indoor fusion positioning method based on improved PDR algorithm
  • Indoor fusion positioning method based on improved PDR algorithm
  • Indoor fusion positioning method based on improved PDR algorithm

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Embodiment Construction

[0086] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0087] see figure 1 , a kind of indoor fusion positioning method based on improved PDR algorithm of the embodiment of the present invention, comprises the following steps:

[0088] S1: When establishing the RSSI offline fingerprint database according to the Wi-Fi signal strength, collect the offline Wi-Fi location fingerprint data, summarize the fingerprint data of all points, and use the physical address of the RSSI signal of the reference point as the identification of the wireless access node (AccessPoint, AP) , taking into account the stability of RSSI, the average value of multiple measurements is used to extract the signal strength characteristics of fingerprint points, and a more accurate fingerprint database is established. The K-Nearest Neighbor (KNN) algorithm and the Weighted K-Nearest Neighbor (WKNN) algorithm have smalle...

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Abstract

The invention provides an indoor fusion positioning method based on an improved PDR algorithm. The method comprises the steps of: using An accelerometer and a gyroscope in a Bluetooth gyroscope sensor for collecting three-axis acceleration, angular velocity, angle and other data for preprocessing; performing stride frequency detection, step length estimation and heading calculation by utilizing data simulation to obtain initial PDR positioning; meanwhile, correcting the positioning information calculated by the PDR algorithm by using the RSSI ranging and positioning measurement value after the WKNN algorithm, and obtaining the final PDR positioning by using the left and right foot coordinate data fusion; and finally, performing fusion positioning by using the EKF as a fusion filter for PDR and RSSI positioning to obtain a final positioning coordinate. The method has the advantages of being small in positioning error, accurate in positioning result and the like, good system stability is shown when the method is applied to the actual environment, the rationality of the algorithm is verified, and the obtained positioning prediction value can provide beneficial guidance for indoor positioning personnel.

Description

technical field [0001] The invention belongs to the technical field of indoor positioning, and in particular relates to an indoor fusion positioning method based on an improved PDR algorithm. Background technique [0002] A method based on inertial sensors, called Pedestrian Dead Reckoning (PDR) positioning, has the advantages of low cost, small size and strong autonomy. After the initial position and direction are given, PDR uses the step size and walking direction to be able to calculate The location and direction information of pedestrians at the next moment, providing pedestrian location information anytime and anywhere. RSSI stands for Received Signal Strength Indication, which is a positioning technology that measures the distance between the signal point and the receiving point by the strength of the received signal, and performs positioning calculations based on the corresponding data. Extended Kalman filter (EKF) is a high-efficiency recursive filter, which uses th...

Claims

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Application Information

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IPC IPC(8): H04W4/02H04W4/021H04W4/33
CPCH04W4/021H04W4/33H04W4/023
Inventor 杨君郭娅婷甘露
Owner WUHAN UNIV OF SCI & TECH
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