High-speed Sigma-gating SMC-PHD filter
High-speed Sigma-gating SMC-PHD filter
复制标题
高速西格玛门控 SMC-PHD 滤波器
DOI：
10.1016/j.sigpro.2013.03.011
复制
发表时间：
2013-09-01
影响因子：
4.4
通讯作者：
Sattar, Tariq Pervez
中科院分区：
文献类型：
--
作者：
Li, Tiancheng;Sun, Shudong;Sattar, Tariq Pervez
为了解决一般的多目标跟踪问题，提出了一种改进的序贯蒙特卡罗(SMC)实现的概率假设密度(PHD)滤波器，称为Sigma-Gating SMC-PHD滤波器，它只使用指定的Sigma门内的局部邻近测量来更新粒子。Sigma门基于给定的测量噪声，例如3 Sigma，其中Sigma是测量噪声的标准差。相应地，提出了基于测量模型累积分布函数的补偿策略。消除位于粒子周围的门外的测量的贡献将极大地减少不必要的计算，从而提高整体处理速度。更重要的是，这可以保护估计不受门外杂波的干扰，从而提供更稳健和准确的估计。特别是当杂波密度较高时，我们的方法可以产生处理效率更快和估计精度更好的双赢(与标准的PHD滤波器相比)。这一点通过分别使用距离测量和方位测量的SMC-PHD滤波器的仿真来证明。(C)2013爱思唯尔B.V.保留所有权利。
To solve the general multi-target tracking (MTT) problem, an improved Sequential Monte Carlo (SMC) implementation of the probability hypothesis density (PHD) filter called as Sigma-gating SMC-PHD filter, is proposed that updates particles only using the local nearby measurements inside a specified sigma-gate. The sigma-gate is based on the given measurement noise, e.g. 3 sigma, where sigma is the standard deviation of the measurement noise. Correspondingly, a compensation strategy based on the cumulative distribution function of the measurement model is suggested. Eliminating the contribution of measurements lying outside the gate around the particle will highly reduce unnecessary computation and thus improve the overall processing speed. More importantly, this could shield the estimate from interference from the clutter outside the gate giving more robust and accurate estimation. Especially when the clutter density is high, our approach can yield a win-win that is much faster processing efficiency and better estimation accuracy (as compared with the standard PHD filter). This is demonstrated by simulations of the SMC-PHD filters using measurements of range and bearing, respectively. (c) 2013 Elsevier B.V. All rights reserved.