一种基于粒子滤波的TBD改进算法  

An Improved TBD Algorithm Based on Particle Filter

作　　者：方中理 邹永显 李璐 袁子乔[1] 王勇[1] FANG Zhongli;ZOU Yongxian;LI Lu;YUAN Ziqiao;WANG Yong(Xi'an Electronic Engineering Research Institute,Xi'an 710100;Army Research Institute,Beijing 100072)

机构地区：[1]西安电子工程研究所,西安710100 [2]陆军研究院,北京100072

出　　处：《火控雷达技术》2024年第1期67-71,共5页Fire Control Radar Technology

摘　　要：在传统基于粒子滤波的检测前跟踪算法中,需要使用大量粒子的概率分布来预测下一时刻目标位置,这就带来了计算量的增加,如果使用的粒子数目少,会导致跟踪的准确性降低,本文使用特征提取分类的方式,在进行目标跟踪之前,对目标和杂波进行分类。以此来缩小粒子生成的范围,从而达到提高算法精度、降低算法复杂度的目的。仿真结果显示,经过改进后的粒子滤波算法的误差有了明显降低,同时,将算法应用在雷达的实测数据上有较好的效果,具有工程应用的价值。In traditional particle filter based TBD algorithm,a large number of particle probability distributions are required to predict the target position at the next moment,which increases the computational complexity.If a small number of particles are used,it can also lead to a decrease in tracking accuracy.In this paper,the traditional particle filter TBD by adding the feature extraction was modified,in which the feature extraction is used to classify the target scope and clutter scope before target tracking to narrow down the scope of particle generation.The simulation results showed that the modified particle filter algorithm had significantly improved tracking performance compared to traditional particle filter algorithms.When the algorithm was applied to radar measured data,it also has good results with engineering application value.

关 键 词：检测前跟踪 粒子滤波 特征提取 

分 类 号：TN95[电子电信—信号与信息处理]