An Adaptive UPF Algorithm for Tracking Maneuvering Target in Compound K Noise Environment

LIU Wang-sheng; LI Ya-an; WANG Ming-huan

doi:10.3969/j.issn.0372-2112.2012.06.029

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An Adaptive UPF Algorithm for Tracking Maneuvering Target in Compound K Noise Environment

更新时间：2025-07-16

- An Adaptive UPF Algorithm for Tracking Maneuvering Target in Compound K Noise Environment
- Acta Electronica Sinica Vol. 40, Issue 6, Pages: 1240-1245(2012)
- 作者机构：
  
  1. 浙江理工大学机械与自动控制学院,浙江,杭州,310012
  2. 西北工业大学航海学院,陕西,西安,710072
  3. 浙江工业大学特种装备制造与先进加工技术教育部重点实验室,浙江,杭州,310012
  4. 浙江理工大学机械与自动控制学院浙江杭州,310012
  5. 西北工业大学航海学院陕西西安,710072
  6. 浙江工业大学特种装备制造与先进加工技术教育部重点实验室浙江杭州,310012
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.51179158, No.51179157, No.50905165);Zhejiang Provincial Open Fund for Key Laboratory of Special Purpose Equipment and Advanced Processing Technology (No.2011EM010)
- DOI：10.3969/j.issn.0372-2112.2012.06.029
  CLC： TN953
- Published：2012
- 稿件说明：
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LIU Wang-sheng, LI Ya-an, WANG Ming-huan. An Adaptive UPF Algorithm for Tracking Maneuvering Target in Compound K Noise Environment[J]. Acta Electronica Sinica, 2012, 40(6): 1240-1245.
DOI：

LIU Wang-sheng, LI Ya-an, WANG Ming-huan. An Adaptive UPF Algorithm for Tracking Maneuvering Target in Compound K Noise Environment[J]. Acta Electronica Sinica, 2012, 40(6): 1240-1245. DOI： 10.3969/j.issn.0372-2112.2012.06.029.

摘要

针对复合

噪声下机动目标跟踪系统具有强非线性非高斯的特点

提出了一种自适应无迹粒子滤波(Adaptive Unscented Particle Filter

AUPF)算法.该算法建立在常加速模型及其改进滤波算法基础上

并将无迹卡尔曼滤波(Unscented Kalman Filter

UKF)与强跟踪滤波(Strong Tracking Filter

STF)算法相结合作为提议分布

提高了系统跟踪一般机动和阶跃机动的能力.在给出复合

噪声模型的基础上

利用AUPF算法对几种典型机动目标进行了计算机仿真

并同无迹粒子滤波(Unscented Particle Filter

UPF)算法进行了比较.仿真结果表明

复合

噪声下AUPF算法能更有效地对各种机动目标进行跟踪

具有较高的跟踪精度.

Abstract

Aimed at the strong nonlinear and non-Gaussian characteristics of maneuvering target tracking system under compound

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

noise.And the co

mparison 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.

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