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未知转换概率矩阵下的机动目标跟踪算法

Study on maneuvering target tracking algorithm with unknown transition probabilities matrix
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摘要 机动目标跟踪过程中的转换概率矩阵往往是未知的,系统状态也将呈现非线性、非高斯、不完全观测的特点。传统的方法如交互多模型、广义伪贝叶斯算法等解决该类型问题的效果并不理想。将准贝叶斯法则和辅助粒子滤波算法相结合,提出了一种新的未知转换概率矩阵条件下的机动目标跟踪算法(QB-APF)。仿真结果表明,该算法与其他方法相比具有更高的滤波精度和较好的数值稳定性。 In practical situations, the transition probability matrix is always unknown during the process of maneuvering target tracking, and the system state is characterized by nonlinear, non-Gaussian and incompletely observed too. The traditional methods such as IMM and GPB deal badly with this kind of problem. Both the quasi-Bayesian algorithm and the auxiliary particle filter algorithm are combined to present a new maneuvering target tracking algorithm called QB-APF with unknown transition probability matrix. Simulation results demonstrate that the QB-APF algorithm improves filtering accuracy and has satisfied numerical stability compared with other algorithms.
作者 李景熹 王树宗 王航宇
机构地区 海军工程大学海军兵器新技术应用研究所 海军工程大学电子工程学院
出处 《系统工程与电子技术》 EI CSCD 北大核心 2008年第7期1214-1217,共4页 Systems Engineering and Electronics
关键词 转换概率矩阵 机动目标跟踪 辅助粒子滤波 多模型 transition probability matrix maneuvering target tracking auxiliary particle filter multiple model
分类号 TP274 [自动化与计算机技术—检测技术与自动化装置]
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参考文献13

  • 1Bar-Shalom Y, Li X R, Kirubarajan T. Estimation with applications to tracking and navigation: theory, algorithms, and software[M]. New York: Wiley, 2001.
  • 2王运锋,刘健波,游志胜,费向东.一种简化的交互多模式算法[J].系统工程与电子技术,2005,27(4):740-743. 被引量：3
  • 3Bar-Shalom Y, Li X R. Multitarget-multisensor tracking: principles and techniques[M]. YBS Publishing, Storrs, CT, 1995.
  • 4Arnaud Doueet, Branko Ristie. Recursive state estimation for multiple switching models with unknown transition probabilities [J]. IEEE Trans. on Aerospace and Electronic Systems, 2002, 38(3) ; 1098 - 1104.
  • 5左东广,韩崇昭,郑林,朱洪艳,卞树檀.基于时变马尔科夫转移概率的机动目标多模型跟踪[J].西安交通大学学报,2003,37(8):824-828. 被引量：18
  • 6Jilkov V P, Li X R. Adaptation of transition probability matrix for multiple model estimators[C] // Proc. of 4th Annual Conference on Information Fusion, 2001 : 250 - 257.
  • 7Rickard Karlsson, Niclas Bergman. Auxiliary particle filters for tracking a maneuvering target[C]//Proc, of the 39 IEEE Conference on Decision and Control Sydney, Australia, 2000:3891 - 3895.
  • 8Li Yanqiu, Yi Shen, Liu Zhlyan. A new smoothing particle filter for tracking a maneuvering target[C] // Proc. of the Second International Conference on Machine Learning and Cybernetics, 2003:1004 - 1008.
  • 9Jilkov Vesselin P, Li X R. Online Bayesian estimation of transition probabilities for markovlan jump systems[J]. IEEE Trans. on Signal Processing, 2004, 52(6) ; 1620 - 1630.
  • 10Gelman A, Carlin J B, Stern H S, et al. Bayesian data analysis [M]. Boca Raton, FL: Chapman & Hall/CRC, 1995.

二级参考文献17

  • 1Bar-shalom Y, Rong L X. Estimation and tracking principles, techniques, and software [M]. Boston. Artech House, 1993.
  • 2Lin H J, Atherton D P. An investigation of the SFIMM algorithm for tracking manoeuvring targets[A]. The 32^nd Conference on Decision and Control,San Antonio,Texas, 1993.
  • 3Munir A, Atherton D P. Adaptive interacting multiple model algorithm for tracking a manoeuvring target[J]. IEE Proceedings of Radar, Sonar and Navigation,1995,142(1):11~17.
  • 4Averbuch A, Itzikowitz S, Kapon T. Radar target tracking---viterbi versus IMM[J]. IEEE Transactiions on Aerospace and Electronic Systems, 1999,27(3):550~563.
  • 5Rabiner L R. A tutorial on hidden Markov model and selected applications in speech recognition[J]. Proceedings of IEEE, 1989,77(2):257~285.
  • 6Baker J K. The dragon system--an overview[J].IEEE Transactions on Acoustics, Speech, Signal Processing, 1975,23(1):24~29.
  • 7Baum L E, Sell G R. Growth functions for transformations on manifolds[J]. Pac J Math, 1968, 27(2).211~227.
  • 8Frenkel L, Feder M. Recursive expectation maximization (EM) algorithms for time-varying parameters with applications to multiple target[J]. IEEE Transactions on Signal Processing,1999,47(2):306~320.
  • 9Wu W R, Chen P P. A nonlinear IMM algorithm for maneuvering target tracking [J].IEEE Transactions on Aerospace and Electronic Systems, 1994,30(3):875~885.
  • 10Bar-Shalom Y, Li X R. Multitarget-multisensor tracking: principles and techniques[M]. YBS Publishing, 1995.

共引文献19

系统工程与电子技术
2008年 第7期

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