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用于纯方位跟踪的简化粒子滤波算法及其硬件实现

洪少华 史治国 陈抗生

洪少华, 史治国, 陈抗生. 用于纯方位跟踪的简化粒子滤波算法及其硬件实现[J]. 电子与信息学报, 2009, 31(1): 96-100. doi: 10.3724/SP.J.1146.2007.01166
引用本文: 洪少华, 史治国, 陈抗生. 用于纯方位跟踪的简化粒子滤波算法及其硬件实现[J]. 电子与信息学报, 2009, 31(1): 96-100. doi: 10.3724/SP.J.1146.2007.01166
Hong Shao-hua, Shi Zhi-guo, Chen Kang-sheng. Simplified Algorithm and Hardware Implementation for Particle Filter Applied to Bearings-only Tracking[J]. Journal of Electronics & Information Technology, 2009, 31(1): 96-100. doi: 10.3724/SP.J.1146.2007.01166
Citation: Hong Shao-hua, Shi Zhi-guo, Chen Kang-sheng. Simplified Algorithm and Hardware Implementation for Particle Filter Applied to Bearings-only Tracking[J]. Journal of Electronics & Information Technology, 2009, 31(1): 96-100. doi: 10.3724/SP.J.1146.2007.01166

用于纯方位跟踪的简化粒子滤波算法及其硬件实现

doi: 10.3724/SP.J.1146.2007.01166

Simplified Algorithm and Hardware Implementation for Particle Filter Applied to Bearings-only Tracking

  • 摘要: 针对粒子滤波运算量大,硬件复杂性高的问题,该文提出了一种用于纯方位跟踪的简化粒子滤波算法,该算法引入了一种新的基于阈值的重采样方法,降低了硬件实现的复杂度。在算法研究的基础上,论文研究了基于FGPA的硬件电路实现方法,给出了系统的整体硬件结构及重采样/采样模块的实现方案,讨论了粒子滤波硬件实现的资源优化及时间优化问题。仿真结果表明,对于纯方位跟踪问题,该粒子滤波算法具有优于扩展Kalman滤波器(EKF)的性能;硬件电路实验表明,该滤波器可以实现对被动目标的纯方位跟踪,并具有比通用粒子滤波器较快的处理速度。
  • Song T L and Speyer J L. A stochastic analysis of a modifiedgain extended Kalman filter with application to estimationwith bearings-only measurements. IEEE Trans. on AutomaticControl, 1985, AC-30(10): 940-949.[2]郭福成, 李宗化, 孙仲康. 无源定位跟踪中修正协方差扩展卡尔曼滤波算法[J].电子与信息学报.2004, 26(6):917-922浏览[3]Ristic B, Arulampalam S, and Gordon N. Beyond theKalman Filter: Particle Filters for Tracking Applications.Boston, London: Artech House, 2004, Chapter 5-12.[4]Doucet A, de Freitas N, and Gordon N (Eds.). SequentialMonte Carlo Methods in Practice. New York: Springer,2001, Chapter 15-26.[5]Doucet A and Wang X D. Monte Carlo methods for signalprocessing: A review in the statistical signal processingcontext. IEEE Signal Processing Magazine, 2005, 22(6):152-170.[6]Gordon N, Salmond D, and Smith A. Novel approach tononlinear/non-Gaussian Bayesian state estimation[J].IEEProceedings on Radar and Signal Processing.1993, 140(2):107-113[7]Zhai Y and Yeary M. A new particle filter tracking algorithmfor DOA sensor system. Proc. of Instrumentation andMeasurement Technology, Warsaw, 2007: 1-4.[8]Bolic M, Athalye A, and Djuric P M, et al.. Algorithmicmodification of particle filters for hardware implementation.Proc. of the European Signal Processing. Conference, Vienna,Austria, 2004: 1641-1646.[9]Bolic M, Djuric P M, and Hong S. Resampling algorithms forparticle filters: A computational complexity perspective.EURASIP Journal of Applied Signal Processing, 2004, (15):2267-2277.[10]Athalye A, Bolic M, and Hong S, et al.. Generic hardwarearchitectures for sampling and resampling in particle filters.EURASIP Journal of Applied Signal Processing, 2005, (17):2888-2902.
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出版历程
  • 收稿日期:  2007-07-16
  • 修回日期:  2008-09-29
  • 刊出日期:  2009-01-19

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