The Analysis and Improvement of a Low-SNR Slow-Moving Point Target Sequential Detection Algorithm

CUI Chang-wei; LIN Ying; CHEN Jing-chun

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The Analysis and Improvement of a Low-SNR Slow-Moving Point Target Sequential Detection Algorithm

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- The Analysis and Improvement of a Low-SNR Slow-Moving Point Target Sequential Detection Algorithm
- Acta Electronica Sinica Vol. 29, Issue 6, Pages: 820-823(2001)
- 作者机构：
  
  1. 北京无线电测量研究所,北京,100854
  2. Syracuse University,Syracuse,NY, U.S.A
  3. 哈尔滨工业大学,哈尔滨,150001
  4. 北京无线电测量研究所北京,100854
  5. Syracuse UniversitySyracuseNY13210- U.S.A
  6. 哈尔滨工业大学哈尔滨,150001
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.7
- Published：2001
- 稿件说明：
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CUI Chang-wei, LIN Ying, CHEN Jing-chun. The Analysis and Improvement of a Low-SNR Slow-Moving Point Target Sequential Detection Algorithm[J]. Acta Electronica Sinica, 2001, 29(6): 820-823.
DOI：

CUI Chang-wei, LIN Ying, CHEN Jing-chun. The Analysis and Improvement of a Low-SNR Slow-Moving Point Target Sequential Detection Algorithm[J]. Acta Electronica Sinica, 2001, 29(6): 820-823. DOI：

摘要

本文主要讨论的是低信噪比红外图像序列中缓动点目标的实时检测问题.在对传统序贯假设检测(正推法)进行了分析后

针对正推法的轨迹交叉和初始点多而引起的组合爆炸等问题

本文给出了一种基于逆推法的统计检测算法

并对如何利用目标的缓动特性和分段技术来提高信噪比

如何表示轨迹等进行了论述.实验结果表明

该算法有较好的性能.

Abstract

Techniques of automatic real-time detection of slow-moving point target in the low SNR infrared image sequences are discussed in this paper.After analysis of the traditional sequential hypothesis testing (forward-hypothesis based)

aiming at the problems of trajectories-cross and combination inflation due to more start points

a backward-hypothesis based statistical detection algorithm is put forward.The paper also discusses the methods to improve SNR and to denote the trajectories.The experimental results show that the algorithm has good performance.

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The Detection Algorithm for Moving Point Target Trajectory in Image Sequences

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