A Multiple Extended Target Multi-Bernouli Filter Based on Star-convex Random Hypersurface Model
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摘要: 针对复杂不确定性环境下具有不规则形状的多扩展目标跟踪问题, 提出了一种基于星凸形随机超曲面模型(Star-convex RHM)的多扩展目标多伯努利滤波算法.首先, 在有限集统计(Finite set statistics, FISST)理论框架下, 采用多伯努利随机有限集(MBer-RFS)和泊松RFS (Possion-RFS)分别描述多扩展目标的状态和观测, 并给出扩展目标势均衡多目标多伯努利(ET-CBMeMBer)滤波器.其次, 利用RHM去描述任意星凸形扩展目标的量测源分布, 提出了容积卡尔曼高斯混合星凸形多扩展目标多伯努利滤波器.此外, 本文给出了一种多扩展目标不规则形状估计性能的评价指标.最后, 通过多扩展目标和具有形状突变的多群目标的跟踪仿真实验验证了本文方法的有效性.Abstract: Considering the tracking of multi-extended target with irregular shape in complicated and uncertain environment, this paper proposes a multi-extended target multi-Bernoulli filtering algorithm based on star-convex random hypersurface model (RHM). First, in the framework of finite set statistics (FISST), the multi-Bernoulli random finite set (MBer-RFS) and Poisson-RFS are used to model multi-extended target state and measurement respectively, and then the extended target cardinality balanced multi-target multi-Bernoulli (ET-CBMeMBer) filter is given. Subsequently, using RHM to represent the measurement source distribution of any star-convex extended target, this paper proposes the cubature Kalman Gaussian mixture Star-convex multi-extended target multi-Bernoulli filter. Besides, this paper also gives a performance metric which can evaluate the irregular shape estimation of multi-extended target. Finally, the effectiveness of the proposed method is verified by the tracking simulations of multi-extended target and multi-group target with sudden shape change.
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Key words:
- Multiple extended target tracking /
- random hypersurface model /
- multi-Bernoulli filter /
- cubature Kalman
1) 本文责任编委 郭戈 -
图 6 两种滤波器的形状估计局部放大图
Fig. 6 The partial enlarged effect of the two filters for shape estimation (ET)
图 12 两种滤波器的对群目标的形状估计局部放大图
Fig. 12 The partial enlarged effect of the two filters for shape estimation (GT)
表 1 多目标初始参数
Table 1 Initial parameters of multi-target
目标 新生时刻(s) 消亡时刻(s) 位置(m) 速度(m/s) 目标1 1 35 $[10, -50]^{\rm T}$ $[10, 2]^{\rm T}$ 目标2 11 50 $[10, 10]^{\rm T}$ $[8, 5]^{\rm T}$ 目标3 26 50 $[10, 50]^{\rm T}$ $[12, 2]^{\rm T}$ 
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