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Track prediction method based on robust regression

A track prediction and robust regression technology, applied in the field of target tracking, can solve problems such as inaccurate prediction, and achieve the effect of improving prediction accuracy and reducing impact.

Active Publication Date: 2021-04-23
BEIJING INST OF ELECTRONICS SYST ENG
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AI Technical Summary

Problems solved by technology

The traditional target track prediction adopts the least square method for track fitting. However, in reality, due to the influence of climate, terrain and interference, the measurement information will inevitably have outliers. The purpose of minimizing the sum of squared residuals has to accommodate outliers, resulting in inaccurate predictions

Method used

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  • Track prediction method based on robust regression
  • Track prediction method based on robust regression
  • Track prediction method based on robust regression

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Embodiment Construction

[0052] In order to make the technical solutions and advantages of the present invention clearer, the implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0053] like figure 1 As shown, a system architecture of a track prediction method based on robust regression that can implement an embodiment of the present invention, the system architecture may include an observation data set 101 and a server 103 . Wherein the information source data set 101 includes several target information sources, the target information source can be any objects with flight tracks such as airplanes and unmanned aerial vehicles, and the server 103 is a server that provides various services, such as providing support for track prediction background server etc.

[0054] like figure 2 As shown, a track prediction method based on robust regression, including:

[0055] S10: Obtain the measurement value of the informatio...

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Abstract

One embodiment of the invention discloses a track prediction method based on robust regression. The method comprises the following steps: S10, obtaining a measurement value of an information source; S13, calculating a prediction coefficient; S15, calculating a weighted prediction coefficient; and S17, judging whether the number of iterations is met or not, if so, ending the process, and if not, carrying out step S15. According to the method, different weights are given to the measurement data according to the measurement residual errors, so that the influence of outliers on prediction is reduced, and the prediction precision is improved.

Description

technical field [0001] The invention relates to the field of target tracking. More specifically, it relates to a method of track prediction based on robust regression Background technique [0002] Target track prediction refers to the prediction of characteristic parameters such as the position state and speed state of the target at the current moment or in the future based on the measurement information of the information source. Target track prediction can predict track status information in advance, providing support for firepower allocation and threat assessment. The traditional target track prediction adopts the least square method for track fitting. However, in reality, due to the influence of climate, terrain and interference, the measurement information will inevitably have outliers. The purpose of minimizing the sum of squared residuals has to accommodate outliers, resulting in inaccurate predictions. Contents of the invention [0003] In view of this, the firs...

Claims

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Application Information

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IPC IPC(8): G01C21/20G01C1/00
CPCG01C21/20G01C1/00
Inventor 张英静邱天权晓岚刘明阳臧振宇吴天昊温嘉奇
Owner BEIJING INST OF ELECTRONICS SYST ENG
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