电子学报2012，Vol.40Issue(6)：1240-1245,6.DOI:10.3969/j.issn.0372-2112.2012.06.029
复合K噪声下机动目标跟踪自适应UPF算法
An Adaptive UPF Algorithm for Tracking Maneuvering Target in Compound K Noise Environment
摘要
Abstract
Aimed at the strong nonlinear and non-Gaussian characteristics of maneuvering target tracking system under compound K noise, an adaptive unscented particle filter (AUPF) algorithm is proposed. Based on constant acceleration (CA) model and its modified filtering algorithm, the algorithm adopts a new proposal distribution which combines unscented Kalman filter (UKF) and strong tracking filter (STF) and enhances the system performance for tracking general mobile and step mobile. The AUPF algorithm is applied to track several kinds of typical maneuvering targets based on the model of compound K noise. And the comparison with the unscented particle filter (UPF) algorithm is given. The simulation results show that AUPF algorithm has good track performance for tracking various maneuvering targets and has high tracking precision.关键词
机动目标/常加速模型/AUPF算法/强跟踪滤波/复合K噪声Key words
maneuvering target/ constant acceleration model/ AUPF algorithm/ strong tracking filter/compound K noise分类
信息技术与安全科学引用本文复制引用
刘望生,李亚安,王明环..复合K噪声下机动目标跟踪自适应UPF算法[J].电子学报,2012,40(6):1240-1245,6.基金项目
国家自然科学基金(No.51179158,No.51179157,No.50905165) （No.51179158,No.51179157,No.50905165）
浙江省特种装备制作与先进加工技术重点实验室开放基金(No.2011EM010) （No.2011EM010）
