Centralized 3D Track Initialization Using Random Hough Transformation

WU Ze-min; ZHANG Lei; LIU Han; TIAN Chang

doi:10.3969/j.issn.0372-2112.2013.05.002

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Centralized 3D Track Initialization Using Random Hough Transformation

更新时间：2025-07-16

- Centralized 3D Track Initialization Using Random Hough Transformation
- Acta Electronica Sinica Vol. 41, Issue 5, Pages: 840-847(2013)
- 作者机构：
  
  1. 解放军理工大学通信工程学院,江苏,南京,210007
  2. 广西南宁警备区,广西,南宁,530023
  3. 解放军理工大学通信工程学院江苏南京,210007
  4. 广西南宁警备区广西南宁,530023
- 作者简介：
- 基金信息：
  
  Aeronautical Science Foundation of China (No.20125186005);National Natural Science Foundation of China (No.61201217)
- DOI：10.3969/j.issn.0372-2112.2013.05.002
  CLC： TN957
- Published：2013
- 稿件说明：
移动端阅览
WU Ze-min, ZHANG Lei, LIU Han, et al. Centralized 3D Track Initialization Using Random Hough Transformation[J]. Acta Electronica Sinica, 2013, 41(5): 840-847.
DOI：

WU Ze-min, ZHANG Lei, LIU Han, et al. Centralized 3D Track Initialization Using Random Hough Transformation[J]. Acta Electronica Sinica, 2013, 41(5): 840-847. DOI： 10.3969/j.issn.0372-2112.2013.05.002.

摘要

本文提出了一种用于三维空间直线航迹起始的集中式Hough变换法.基于三维直线的Roberts表示法

设计了Roberts参数相似性判决的假设检验方法.通过对多传感器点迹的随机采样

计算每次采样确定的直线Roberts参数

然后以相似性测度实现Roberts参数的合并

当参数累积超过规定的门限后能可靠地起始一条直线航迹.为了减少无意义的随机采样和不合理的Roberts参数合并

在算法实时过程中适时地检查目标运动速度限制

加快了采样速度

减少了航迹误起始的概率.通过仿真

该算法能适应多传感器多目标环境中传感器数据更新率不同和密集杂波、强干扰的复杂情况.

Abstract

A centralized hough track initialization algorithm is introduced for line in 3 dimensions space.Based on Roberts representation of 3D line

the hypothesis statistics is designed for Roberts parameters similarity.Through random sampling data from multiple sensors

the candidate Roberts parameter for 3D line is created corresponding to the data samples.Similar Roberts parameters are merged to accumulate to proper detection threshold for valid and credible line track.To reduce unreasonable random sampling and improper Roberts parameter merging

the object moving speed constrains are check when algorithm is realized

which will not only speeds up algorithm

but also decreases track false alarm ratio.Through performance analysis from simulation

our 3D centralized hough algorithm can be adapted to multi-sensor

multi-object environment

where different data updating rates

dense clutter and strong jamming will be encountered.

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