一种基于极化分解特征和SVDD的扩展目标检测算法

李强; 姚远昕; 孔祥琦

doi:10.11959/j.issn.1000-0801.2023197

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一种基于极化分解特征和SVDD的扩展目标检测算法

研究与开发 | 更新时间：2024-06-05

- 一种基于极化分解特征和SVDD的扩展目标检测算法
- A range spread target detection algorithm based on polarimetric features and SVDD
- 电信科学 2023年39卷第10期页码：64-73
- 作者机构：
  
  1. 工业和信息化部机关服务局，北京 100804
  2. 中国信息通信研究院西部分院，重庆 401336
  3. 国家无线电监测中心检测中心，北京 100041
- 作者简介：
  
  [ "李强（1976- ），男，工业和信息化部机关服务局高级工程师，主要研究方向为计算机技术、软件工程、无线电技术等" ]
  [ "姚远昕（1996- ），男，中国信息通信研究院西部分院工程师，主要研究方向为无线电频谱规划、国内外无线电管理相关政策" ]
  [ "孔祥琦（1995- ），女，国家无线电监测中心检测中心工程师，主要研究方向为无线电设备检测、无线电频谱管理等" ]
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2023197
  中图分类号： TN956
- 网络出版日期：2023-10，
  
  纸质出版日期：2023-10-20
- 稿件说明：
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李强, 姚远昕, 孔祥琦. 一种基于极化分解特征和SVDD的扩展目标检测算法[J]. 电信科学, 2023,39(10):64-73.

Qiang LI, Yuanxin YAO, Xiangqi KONG. A range spread target detection algorithm based on polarimetric features and SVDD[J]. Telecommunications science, 2023, 39(10): 64-73.
李强, 姚远昕, 孔祥琦. 一种基于极化分解特征和SVDD的扩展目标检测算法[J]. 电信科学, 2023,39(10):64-73. DOI： 10.11959/j.issn.1000-0801.2023197.

Qiang LI, Yuanxin YAO, Xiangqi KONG. A range spread target detection algorithm based on polarimetric features and SVDD[J]. Telecommunications science, 2023, 39(10): 64-73. DOI： 10.11959/j.issn.1000-0801.2023197.

摘要

多极化距离高分辨雷达是地面静止目标检测的重要手段，其回波中目标占据多个距离单元，成为扩展目标。传统基于回波能量的扩展目标检测方法的性能随信杂比的降低而下降。提出一种基于极化分解特征的扩展目标检测算法，利用目标和杂波之间的极化散射特性差异提升低信杂比下的检测性能。所提方法提取16 种极化分解特征组成特征向量作为检测统计量，再使用支持向量数据描述（SVDD）算法估计判别门限。在判别门限的训练阶段，杂波数据的极化分解特征被提取用作训练数据。并且为保证虚警概率，在SVDD的目标函数中引入了两个惩罚参数。使用实测数据进行了实验验证，所提方法在戈壁背景、虚警概率为 10

-4

、检测概率为90%的情况下，所需信杂比约为12.6 dB，相较于基于能量的对比方法降低约1.7 dB。

Abstract

Multi-polarization range high resolution radar is an important mean for ground target detection.In the echo formed by it

the target occupies multiple range cells and becomes an extended target.The traditional spread target detection method relies on energy

and the detection performance decreases when the signal-to-clutter ratio decreases.A spread target detection algorithm based on polarization decomposition features was proposed

whi

ch improved the detection performance under low signal-to-clutter ratio by using the difference of polarization scattering characteristics between target and clutter.Specifically

16 kinds of polarization decomposition features were extracted to form feature vectors as detection statistics

and then support vector data description (SVDD) was used to obtain the detection threshold.When training the detection threshold

the polarization decomposition features of clutter were extracted as training data.In order to ensure the false alarm probability

two penalty parameters were introduced into the objective function of SVDD.The experimental results show that the proposed method requires a signal-to-clutter ratio of about 12.6 dB in the case of Gobi background

false alarm probability of 10

-4

and detection probability of 90%

which is about 1.7 dB lower than the energy-based methods.

关键词

Keywords

references

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