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Distributed space-time correlation model trajectory tracking method based on statistical inference

A time-space correlation and statistical inference technology, applied to radio wave measurement systems, measurement devices, instruments, etc., can solve problems such as easy accumulation of errors, low trajectory tracking accuracy, and poor environmental adaptability

Inactive Publication Date: 2016-12-28
INNER MONGOLIA UNIV OF TECH
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Problems solved by technology

The main problem of this method is that the RSSI ranging model is affected by various factors such as the field environment, multipath, diffraction, and measurement technology, resulting in strong time-varying characteristics, and its positioning accuracy is relatively low, and the positioning success rate is not high.
[0006] The existing wireless sensor network trajectory tracking method is to form a trajectory through continuous positioning, which does not make full use of the statistical characteristics of the probability distribution of the positioning information of adjacent beacon nodes within a certain space within a certain period of time and the local space contained in the topology of the wireless network. Information, the existing methods have poor adaptability to the environment, errors are easy to accumulate, and the accuracy of trajectory tracking is low

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  • Distributed space-time correlation model trajectory tracking method based on statistical inference
  • Distributed space-time correlation model trajectory tracking method based on statistical inference
  • Distributed space-time correlation model trajectory tracking method based on statistical inference

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Embodiment Construction

[0055] The present invention will be further elaborated below in conjunction with the accompanying drawings of the description.

[0056] The trajectory tracking method of the distributed spatio-temporal association model based on statistical inference of the present invention comprises the following steps:

[0057] In the positioning space, beacon nodes are deployed in a grid at equal intervals in the vertical and horizontal directions, and the beacon node information {Node ID , (x, y)} are stored at each unknown node, forming area information and boundary information at the unknown node, where Node ID is the Id number of the beacon node, and (x, y) is its coordinate;

[0058] The beacon node that receives the notification information sent by the unknown node transmits the positioning signal at a fixed frequency, and the unknown node receives and forms multiple time series R according to the beacon node i ;

[0059] Each unknown node constructs the boundary time series, det...

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Abstract

The invention relates to a distributed space-time correlation model trajectory tracking method based on statistical inference. Beacon nodes are deployed in the shape of an equidistant grid in a locating space according to longitudinal and transverse directions, and beacon node information is saved in each unknown node; the beacon nodes receiving notification information transmitted by the unknown nodes emit locating signals at a fixed frequency, and the unknown nodes receive and form multiple time sequences according to the beacon nodes; each unknown node constructs a boundary time sequence to detect a boundary crossing event and determine a corresponding time point; each unknown node constructs regional time window statistical quantity and infers the current region; the position of the intersection points of the trajectories and the boundary is inferred; and the trajectories are formed and the result is uploaded to aggregation nodes. According to the method, RSSI locating information probability distribution characteristics in the trajectory tracking problem and space-time data mining are overall considered, and the boundary crossing event and regional information are discovered through the method of time-space information statistical inference so that trajectory tracking can be realized.

Description

technical field [0001] The invention relates to a wireless sensor network monitoring technology, in particular to a track tracking method of a distributed time-space correlation model based on statistical inference. Background technique [0002] Due to its low cost, simple deployment, and unaffected by visibility conditions, WSN (WirelessSensor Network) is widely used in various indoor monitoring systems, including coal mine safety production monitoring systems, subway construction safety real-time early warning systems, and indoor precise navigation system etc. Indoor applications of wireless sensor networks are still expanding rapidly. [0003] For many indoor applications, the trajectory of the target is the most basic information, which is the basis for the realization of LBS (Location Based Service). For example, in the coal mine safety production monitoring system, the trajectory of personnel and mobile equipment is an important monitoring content; in the subway cons...

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Application Information

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IPC IPC(8): G01S5/02
CPCG01S5/0278G01S5/0294
Inventor 秦俊平李洋刘利民田永红
Owner INNER MONGOLIA UNIV OF TECH
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