Convolution Kernel Implementation Based on Quasi-Monte Carlo Probability Hypothesis Density

MA Yue; QIN Qian-qing; ZHU Jian-zhang; HU Yi-jun

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Convolution Kernel Implementation Based on Quasi-Monte Carlo Probability Hypothesis Density

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- Convolution Kernel Implementation Based on Quasi-Monte Carlo Probability Hypothesis Density
- Acta Electronica Sinica Vol. 39, Issue 3A, Pages: 64-68(2011)
- 作者机构：
  
  1. 武汉大学数学与统计学院,湖北,武汉,430072
  2. 武汉大学测绘遥感信息工程国家重点实验室,湖北,武汉,430072
  3. 解放军信息工程大学信息工程学院,河南,郑州,450002
  4. 武汉大学数学与统计学院湖北武汉,430072
  5. 武汉大学测绘遥感信息工程国家重点实验室湖北武汉,430072
  6. 解放军信息工程大学信息工程学院河南郑州,450002
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN953
- Published：2011
- 稿件说明：
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MA Yue, QIN Qian-qing, ZHU Jian-zhang, et al. Convolution Kernel Implementation Based on Quasi-Monte Carlo Probability Hypothesis Density[J]. Acta Electronica Sinica, 2011, 39(3A): 64-68.
DOI：

MA Yue, QIN Qian-qing, ZHU Jian-zhang, et al. Convolution Kernel Implementation Based on Quasi-Monte Carlo Probability Hypothesis Density[J]. Acta Electronica Sinica, 2011, 39(3A): 64-68. DOI：

摘要

本文提出了两种新的算法.第一

拟蒙特卡罗概率假设密度(QMC-PHD)滤波

主要思想是利用QMC方法来实现PHD滤波.在仿真实验中可以发现:在目标数目和状态估计方面

新算法比序贯蒙特卡罗概率假设密度(SMC-PHD)滤波器更精确.第二

卷积核拟蒙特卡罗概率假设密度滤波(CKQMC-PHD)

主要思想是基于QMC-PHD滤波的基础之上引入卷积核(CK)的估计算法.当观测噪声变小的时候

CKQMC-PHD滤波还能够很好地估计出目标状态和目标数目

其表现要明显的好于QMC-PHD滤波.仿真实验也证明了CKQMC-PHD滤波的估计效果.

Abstract

In this paper

we propose two algorithms.The first one is the quasi-Monte Carlo probability hypothesis density filter (PHD).Quasi-Monte Carlo is used to implement the PHD filter.In the simulation

we can find that the proposed algorithm is more accurate than the sequential Monte Carlo PHD filter in the estimation of target state and the number of targets.The second algorithm is convolution kernel quasi-Monte Carlo PHD (CKQMC-PHD) filter.The convolution kernel algorithm is used in the QMC-PHD filter.When the observation noise becomes small

CKQMC-PHD filter is very efficient to estimate the state and the number of targets

the behave of the CKQMC-PHD filter is better than that of QMC-PHD filter.The simulation results prove the effect of the CKQMC-PHD filter.

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