摘要
脉冲多普勒(Pulse Doppler,PD)雷达会产生距离模糊和多普勒模糊问题,传统方法通过发射多个脉冲重复频率(Pulse Repetition Frequency,PRF)并相互关联来解模糊。但当信噪比较低时,为确保检测到目标需采用低门限而产生了大量虚警,传统方法由于数据关联导致计算复杂度过高而失效,基于随机有限集的势均衡多伯努利(Cardinality Balanced Multi-target Multi-Bernoulli,CBMeMBer)滤波器可有效解决该问题。本文在贝叶斯框架下采用CBMeMBer滤波器进行目标数目估计和距离多普勒解模糊,并针对模型非线性问题提出了一种基于自适应新生密度的序贯蒙特卡罗(Sequential Monte Carlo,SMC)实现方法。仿真结果表明,该滤波器在密集虚警下依然能利用模糊量测对多个目标实现联合检测与解模糊,且性能优于基于自适应新生密度的集势概率假设密度滤波器(Cardinalized Probability Hypothesis Density,CPHD)。
Pulse Doppler(PD)radar will produce range ambiguity and Doppler ambiguity problems. The traditional method is to transmit multiple pulse repetition frequencies(PRFs)and correlate them to solve the ambiguity.However,when the signal-to-noise ratio is low,a large number of false alarms are generated. To ensure the detection of targets by using low threshold. The Traditional method fails to solve the ambiguity because of the high computational complexity caused by data association, the cardinality balanced multi-target multi-Bernoulli(CBMeMBer)based on random finite set can effectively solve this problem. In this paper,the CBMeMBer filter is used to estimate the number of targets and solve ambiguity in Bayesian framework,Aiming at the nonlinear problem of the model,a sequential Monte Carlo(SMC) implementation method based on adaptive newborn density is proposed. Simulation results showed that the proposed filter can achieve joint detection and estimation of multiple targets using ambiguous measurements containing densely distributed false alarms,and its performance was better than cardinalized probability hypothesis density(CPHD).
作者
董文豪
汪静怡
宋志勇
付强
DONG Wenhao;WANG Jingyi;SONG Zhiyong;FU Qiang(National Key Laboratory of Science and Technology on Automatic Target Recognition,College of Electronic Science,National University of Defense Technology,Changsha,Hunan 410073,China)
出处
《信号处理》
CSCD
北大核心
2022年第3期474-482,共9页
Journal of Signal Processing
基金
国家自然科学基金(61401475)。
关键词
距离模糊
多普勒模糊
势均衡多伯努利
随机有限集
自适应新生密度
range ambiguity
Doppler ambiguity
cardinality balanced multi-target multi-Bernoulli
random finite set
adaptive birth density
