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Method for estimating indoor pedestrian combination poses based on multi-particle swarm optimized

A pose estimation and multi-particle technology, applied in positioning, instruments, measuring devices, etc., can solve problems such as easy misjudgment, wrong positioning results, and increased deployment costs

Active Publication Date: 2019-02-01
SOUTHEAST UNIV
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Problems solved by technology

However, this method needs to deploy more Bluetooth nodes, which increases the deployment cost; and it is easy to misjudgment in indoor environments, such as predicting the target on one side of the wall to the room on the other side of the wall, resulting in wrong positioning results

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  • Method for estimating indoor pedestrian combination poses based on multi-particle swarm optimized
  • Method for estimating indoor pedestrian combination poses based on multi-particle swarm optimized
  • Method for estimating indoor pedestrian combination poses based on multi-particle swarm optimized

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Embodiment Construction

[0075] The present invention will be further described below in conjunction with the accompanying drawings.

[0076] Such as Figure 1-6 As shown, the technical solution adopted in the present invention is: a method for estimating the combined pose of indoor pedestrians based on multi-particle swarm optimization, the method adopts the following steps:

[0077] Step 1: In the WiFi-based fingerprint positioning system, the positioning algorithm adopted is a combination of the random forest classification algorithm and the improved nearest neighbor (KNN) algorithm, such as figure 2 As shown, the algorithm mainly includes the following two steps:

[0078] (1) In the offline stage, the BSSID names and WiFi signal strengths of WiFi nodes that can be received by multiple reference points are collected and stored in the WiFi fingerprint database. Use the random forest classification algorithm to train the collected WiFi fingerprint information in blocks, and save the training resul...

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Abstract

The invention discloses a method for estimating indoor pedestrian combination poses based on a multi-particle swarm optimized. The method comprises the following steps of: using a WiFi-RSS fingerprintidentification method to obtain a WiFi positioning result; using a micro-inertial sensor pedestrian trajectory reckoning method to obtain a pedestrian poses result; using a Bluetooth signal strengthconstraint method to constrain the pedestrian movement range to determine whether the pedestrian is within the communication range of nodes; using a map matching method of the indoor map to constrainthe WiFi positioning result and a pedestrian track reckoning result; using a multi-particle swarm recursive Bayesian filtering method to perform nonlinear non-Gaussian data fusion on the WiFi positioning result, the pedestrian poses result, the pedestrian movement range constraint result, and the map matching method result; finally, obtaining the pedestrian position poses information. According tothe method for estimating the indoor pedestrian combination poses based on the multi-particle swarm optimized, the multi-source information of WiFi-RSS fingerprint, PDR, and MM is fused, and gross and cumulative errors of a filter are eliminated by using the Bluetooth information. The multi-source information fusion is used to optimize the weight and distribution of the particle swarm to improvethe accuracy, reliability, and real-time capability of the indoor pedestrian poses estimation.

Description

technical field [0001] The invention relates to an indoor pedestrian combination pose estimation method based on multi-particle swarm optimization, and belongs to the technical field of pedestrian autonomous navigation and positioning. Background technique [0002] Positioning technology is one of the key technologies of Location Based Service (LBS). Since the propagation of satellite signals is easily interfered by indoor complex environments, positioning and navigation based on satellite signals are not suitable for indoor positioning. Therefore, this requires other positioning solutions for indoor positioning and navigation. At present, common indoor positioning technologies mainly include indoor positioning technology based on wireless network, indoor positioning technology based on radio frequency signal, indoor positioning technology based on computer vision and indoor positioning technology based on inertial sensor. [0003] Due to the abundance of indoor WiFi signa...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S5/02
CPCG01S5/0247G01S5/0252G01S5/0257
Inventor 阳媛戴鹏张晶晶
Owner SOUTHEAST UNIV
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