A Deep Learning Track Correlation Method

CUI Ya-qi; HE You; TANG Tian-tian; XIONG Wei

doi:10.12263/DZXB.20200299

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A Deep Learning Track Correlation Method

CORRESPONDENCE | 更新时间：2025-12-11

- A Deep Learning Track Correlation Method
- ACTA ELECTRONICA SINICA Vol. 50, Issue 3, Pages: 759-763(2022)
- 作者机构：
  
  海军航空大学信息融合研究所，山东烟台 264001
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20200299
  CLC： TP953;TN957
- Received：27 March 2020，
  
  Revised：2021-03-05，
  
  Published：25 March 2022
- 稿件说明：
移动端阅览
崔亚奇,何友,唐田田等.一种深度学习航迹关联方法[J].电子学报,2022,50(03):759-763.

CUI Ya-qi,HE You,TANG Tian-tian,et al.A Deep Learning Track Correlation Method[J].ACTA ELECTRONICA SINICA,2022,50(03):759-763.
崔亚奇,何友,唐田田等.一种深度学习航迹关联方法[J].电子学报,2022,50(03):759-763. DOI： 10.12263/DZXB.20200299.

CUI Ya-qi,HE You,TANG Tian-tian,et al.A Deep Learning Track Correlation Method[J].ACTA ELECTRONICA SINICA,2022,50(03):759-763. DOI： 10.12263/DZXB.20200299.

摘要

根据机器学习当中的理论方法，通过输入和输出数据设计，把信息融合领域的航迹关联问题，转换为机器学习领域中的分类识别问题，研究提出了一种深度学习航迹关联方法.仿真结果表明：所提方法在关联性能和自适应能力方面优于对比方法，具有较好的应用前景.

Abstract

According to the theories and methods in machine learning

we converted the track correlation problem in the field of information fusion to a classification recognition problem in the field of machine learning by designing the input data and output data. In advance

a deep learning track correlation method was proposed in this paper. The experiments illustrate that the new method is better than the compared methods in the aspect of correlation performance and adaptation abilities. Thus

the new method would have a good applied foreground.

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references

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