典型文献
Generalized labeled multi-Bernoulli filter with signal features of unknown emitters
文献摘要:
A novel algorithm that combines the generalized labeled multi-Bernoulli(GLMB)filter with signal features of the unknown emitter is proposed in this paper.In complex electromagnetic environments,emitter features(EFs)are often unknown and time-varying.Aiming at the unknown feature problem,we propose a method for identifying EFs based on dynamic clustering of data fields.Because EFs are time-varying and the probability distribution is unknown,an improved fuzzy C-means algorithm is proposed to calculate the correlation coefficients between the target and measurements,to approximate the EF likelihood function.On this basis,the EF likelihood function is integrated into the recursive GLMB filter process to obtain the new prediction and update equations.Simulation results show that the proposed method can improve the tracking performance of multiple targets,especially in heavy clutter environments.
文献关键词:
中图分类号:
作者姓名:
Qiang GUO;Long TENG;Xinliang WU;Wenming SONG;Dayu HUANG
作者机构:
College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China;China National Aeronautical Radio Electronics Research Institute,Shanghai 200233,China
文献出处:
引用格式:
[1]Qiang GUO;Long TENG;Xinliang WU;Wenming SONG;Dayu HUANG-.Generalized labeled multi-Bernoulli filter with signal features of unknown emitters)[J].信息与电子工程前沿(英文),2022(12):1871-1880
A类:
GLMB
B类:
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AB值:
0.529015
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