| 引用本文: | 陈辉,韩崇昭.Rao-Blackwellized粒子势均衡多目标多伯努利滤波器[J].控制理论与应用,2016,33(2):146~153.[点击复制] |
| CHEN Hui,HAN Chong-zhao.Rao-Blackwellized particle cardinality balanced multi-target multi-Bernoulli filter[J].Control Theory and Technology,2016,33(2):146~153.[点击复制] |
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| Rao-Blackwellized粒子势均衡多目标多伯努利滤波器 |
| Rao-Blackwellized particle cardinality balanced multi-target multi-Bernoulli filter |
| 摘要点击 3597 全文点击 2080 投稿时间：2015-07-05 修订日期：2015-09-28 |
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| DOI编号 10.7641/CTA.2016.50588 |
| 2016,33(2):146-153 |
| 中文关键词 多目标跟踪 多伯努利 随机有限集 粒子滤波 Rao-Blackwell |
| 英文关键词 multi-target tracking multi-Bernoulli random finite set particle filter Rao-Blackwell |
| 基金项目 国家重点基础研究发展计划(“973”计划)(2013CB329405), 国家自然科学基金创新研究群体项目(61221063), 国家自然科学基金项目(61370037, 61005026, 61473217), 甘肃省高等学校科研项目(2014A–035), 甘肃省自然科学基金(1506RJZA090)资助. |
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| 中文摘要 |
| 由于多伯努利滤波器直接近似递推了多目标状态的后验概率密度, 使得多目标跟踪问题在基于随机有限
集理论框架下的求解及目标状态的估计显得更为直观. 本文针对一个状态可分解(线性/非线性)的状态空间模型, 分
析基于Rao-Blackwell定理的滤波估计方法, 结合噪声的去相关构造线性状态的滤波方程. 文中详细推导并提
出Rao-Blackwellized粒子势均衡多目标多伯努利滤波器的一般实现形式, 包括给出多伯努利非线性状态粒子滤波
的实现形式, 并结合非线性滤波结果给出多伯努利线性状态的递推滤波公式. 本文提出的滤波器实现方法能够在
更低维的状态空间上进行采样, 滤波器的整体跟踪性能得到提高. 多目标跟踪的仿真实验结果验证了该算法的有
效性. |
| 英文摘要 |
| The multi-Bernoulli filter propagates approximately the multi-target posterior density so that solving target
tracking problem and extracting target state based on random finite set are more tractable. Considering a state space model
whose state can be divided into linear and nonlinear part, this paper analyzes the Rao-Blackwell theorem based filtering
algorithm. Then, using the corresponding algorithm of decorrelation of state noises, we presents the filtering formula for
linear state. Moreover, this paper proposes a Rao-Blackwellized particle cardinality balanced multi-target multi-Bernoulli
filter. This algorithm firstly implements the particle filtering for multi-Bernoulli nonlinear state, and the filtering formula
of multi-Bernoulli linear state is derived afterwards based on the nonlinear filtering result. The proposed filter can sample
particle in a lower dimensional state space and improve the overall target tracking performance. The simulation results of
the multi-target tracking show the effectiveness of the proposed approach. |