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Consistency target tracking method based on data driving

A target tracking and data-driven technology, applied in the field of target tracking, can solve the problems of high consistency processing and difficult model acquisition

Active Publication Date: 2020-10-27
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0004] In order to overcome the problems of difficult acquisition of models and high computational complexity of consistent processing in the current tracking problem, the present invention proposes a method of using time function curve to fit the observation trajectory, and then make each sensor achieve data consistency as soon as possible according to the sensor position distribution. The processing method improves the tracking accuracy and ensures the reliability of subsequent operations

Method used

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  • Consistency target tracking method based on data driving
  • Consistency target tracking method based on data driving
  • Consistency target tracking method based on data driving

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Embodiment Construction

[0053] The present invention will be further described below in conjunction with accompanying drawings and examples.

[0054] refer to Figure 1 to Figure 7 , a data-driven approach to consistent object tracking, including the following steps:

[0055] Step 1: Define the representation of the observation sequence according to the target Obtain the corresponding topology map according to the obtained sensor node settings;

[0056] Such as figure 1 As shown in , the entire sensor observation system is composed of four sensors, all of which can obtain the position information of the observed target Where i=1, 2, 3, 4, the observation data of each sensor is defined by the following formula

[0057]

[0058] The relationship between the observed data of a single node and the actual data is as follows

[0059]

[0060] in Indicates the observation value of the sensor node numbered i at time k, x k ,y k Indicates the position of the target in the horizontal and verti...

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Abstract

A consistency target tracking method based on data driving comprises the steps: sorting and defining data sequences of all nodes, initializing system parameters, and knowing node position distribution; matching a time function with the node data, and converting node distribution into a form of a general network topological graph; respectively carrying out optimization calculation to obtain fittingparameters of each function; then, selecting time t and substituting the time t into the fitting function to obtain estimated data of each node, and obtaining a corresponding Laplace matrix through the topological graph; and obtaining a weight matrix through calculation of the Laplace matrix, and substituting the weight matrix into an iterative algorithm to enable the node data to be consistent as soon as possible. Aiming at a model-free moving target, the method obtains state estimation through a time function fitting method based on data and distribution positions of multiple sensors, and then, makes data of all nodes be consistent rapidly according to node position calculation; and the sensor interaction technology is effectively utilized, and the estimation precision is improved.

Description

technical field [0001] The invention belongs to the field of target tracking, and relates to estimating the target trajectory by using the measured values ​​of multiple sensor nodes, and then making the estimation of each node consistent by means of distributed calculation. Background technique [0002] In recent years, with the rapid development of sensors and communication technologies, research results in the field of target tracking are changing rapidly, and are widely used in practical applications such as robot collaborative work, Internet of Vehicles, and security monitoring. Generally, most existing target tracking algorithms can be divided into two categories. One is based on "model-driven". First, the single-model or multi-model method is used to match the target's motion state, and then the calculation is performed according to the matching model to obtain the target's motion Trajectories; the other is "data-driven" that relies on observation data, using maximum l...

Claims

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Application Information

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IPC IPC(8): G01C21/20G06F17/16G06F17/17
CPCG01C21/20G06F17/16G06F17/17
Inventor 陈博岳凯王如生俞钡钡鲍元康
Owner ZHEJIANG UNIV OF TECH
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