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基于粒子滤波的水下目标被动跟踪算法 被引量：5

Underwater target passive tracking based on particle filter
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摘要 针对水下被动目标跟踪的非高斯噪声环境和弱可观性的特点,提出了将粒子滤波算法应用于水下被动目标跟踪中的非线性问题,克服了常规的线性化方法易发散且跟踪精度低、误差大的缺点.仿真结果表明:粒子滤波算法提高了滤波的稳定性,跟踪精度优于扩展卡尔曼滤波算法和无迹卡尔曼滤波算法,收到了良好的效果,具有较高的实用价值. Considering the nonlinear non-Gaussian and weak observation of the underwater target passive tracking,the particle filter algorithm was studied and used to the problems in this paper.The proposed algorithm could overcome the conventional linear methods′shortcomings,such as easy divergence,low tracking accuracy,and large error.Simulation results show that the particle filter can enhance the stability of the filtering,and its tracking accuracy is better than EKF and UKF algorithms.
作者 章飞 孙睿
机构地区 江苏科技大学电子信息学院
出处 《江苏科技大学学报（自然科学版）》 CAS 北大核心 2010年第1期83-87,共5页 Journal of Jiangsu University of Science and Technology:Natural Science Edition
基金 海军装备预研基金资助项目(2010401010202)
关键词 粒子滤波 纯方位 被动跟踪 非线性滤波 水下目标 particle filter bearings-only passive tracking nonlinear filtering underwater target
分类号 TP274 [自动化与计算机技术—检测技术与自动化装置]
  • 相关文献

参考文献12

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二级参考文献95

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共引文献241

同被引文献42

  • 1高怡,高社生,吴佳鹏.衰减记忆平方根UPF算法及其在组合导航中的应用[J].中国惯性技术学报,2014,12(6):777-781. 被引量：4
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引证文献5

二级引证文献12

江苏科技大学学报（自然科学版）
2010年 第1期

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