基于DBSCAN聚类和曲线拟合的PRI分选算法  

A PRI Sorting Algorithm Based on DBSCAN Clustering and Curve Fitting Algorithm

作　　者：常安琪 乔宏乐[1] 徐伟[1] CHANG Anqi;QIAO Hongle;XU Wei(Xi'an Electronic Engineering Research Institute,Xi'an 710100)

机构地区：[1]西安电子工程研究所,西安710100

出　　处：《火控雷达技术》2023年第2期21-26,共6页Fire Control Radar Technology

摘　　要：随着电磁环境日益复杂多变,正确的雷达信号分选显得尤为重要。脉冲重复周期(Pulse Repetition Interval,PRI)作为雷达信号分类识别时的典型参数,可用于从交叠信号中分离出不同的雷达脉冲序列。针对高密度脉冲流条件下的PRI分选问题,本文将带噪声的基于密度聚类(Density-Based Spatial Clustering of Application with Noise,DBSCAN)算法与曲线拟合算法相结合,通过Matlab仿真分析对比了其与经典序列差值直方图算法(Sequential Difference Histogram,SDIF)算法的分选正确率和抗噪性能,证明所提方法不仅能得出较高精度的脉冲序列测量值,且分选正确率更高。Since the electromagnetic environment is increasingly complex and more changeable,sorting radar signal correctly is particularly important.Pulse Repetition Interval(PRI),a typical parameter for radar signal classification and recognition,can be used for separating different radar pulse sequences from overlapping signals.Aiming at the PRI sorting under the condition of high-density pulse flow,this paper combines Density-Based Spatial Clustering of Application with Noise(DBSCAN)with curve fitting algorithm.Its sorting accuracy and anti-noise performance are compared with the classical Sequential Difference Histogram(SDIF)algorithm through MATLAB simulation.The results show that the proposed method can not only obtain high-precision pulse sequence measurements,but also reach higher sorting accuracy.

关 键 词：DBSCAN 曲线拟合 SDIF PRI 

分 类 号：TN95[电子电信—信号与信息处理]