基于SPWVD-STFT的海面弱目标检测方法
Sea-Surface Weak Target Detection Method Based on SPWVD-STFT
成怡 1王阳2
作者信息
- 1. 天津工业大学 控制科学与工程学院,天津 300387;天津工业大学 天津市电气装备智能控制重点实验室,天津 300387
- 2. 天津工业大学 控制科学与工程学院,天津 300387
- 折叠
摘要
为了进一步提升时频域特征检测海面弱目标的能力,提出一种平滑伪魏格纳-威利分布(smoothed pseudo Wigner-Ville distribution,SPWVD)-短时傅里叶变换(short-time Fourier transform,STFT)海面弱目标检测算法.首先,采用STFT对回波信号进行时频特征分析,优化SPWVD的时频特征分析结果,并引入K-medoids聚类算法对二者时频矩阵进行降噪处理.然后,提取时频域特征多普勒频率稳定度(Doppler frequency stability,DFS),利用快速凸包学习算法获得虚警可控的判决区域,从而判定海杂波与目标.最后,基于IPIX数据集中实测数据的实验结果表明所提出的检测算法在相同虚警率下比时频三特征检测器的平均检测概率高6.3%.
Abstract
To further improve the capability of time-frequency domain features to detect weak targets on the sea-surface,a smoothed pseudo Wigner-Ville distribution(SPWVD)-short-time Fourier transform(STFT)sea-surface weak target detection algorithm is proposed.Firstly,STFT is adopted to perform time-frequency features analysis on the echo signals,and to optimize the time-frequency features analysis results of SPWVD.The K-medoids clustering algorithm is introduced to denoise the time-frequency matrix.Then,the time-frequency features Doppler frequency stability(DFS)is extracted,and the fast convex hull learning algorithm is utilized to obtain the false alarm controllable judgment region,so as to determine the sea clutter and the target.Finally,results of experiments based on Ice multiparameter imaging X-Band radar(IPIX)measured data show that the detection probability of the proposed detection algorithm is 6.3%higher than that of the time-frequency tri-feature detector at the same false alarm rate.
关键词
海杂波/弱目标检测/时频分析/K-medoids聚类/凸包检测器Key words
sea clutter/weak target detection/time-frequency analysis/K-medoids clustering/convex hull detector引用本文复制引用
出版年
2024
NETL
NSTL
万方数据