改进的马尔可夫参数自适应IMM算法

doi:10.3969/j.issn.0372-2112.2017.05.024

电子学报 ›› 2017, Vol. 45 ›› Issue (5): 1198-1205.DOI: 10.3969/j.issn.0372-2112.2017.05.024

改进的马尔可夫参数自适应IMM算法

戴定成¹, 姚敏立¹, 蔡宗平², 何恒¹

1. 火箭军工程大学信息工程系, 陕西西安 710025;
2. 火箭军工程大学自动化系, 陕西西安 710025

收稿日期:2015-11-18 修回日期:2016-03-01 出版日期:2017-05-25
- 作者简介:
- 戴定成 男,1991年生于湖北麻城.火箭军工程大学信息工程系博士研究生,研究方向为雷达信号处理.E-mail:ddc264@163.com;姚敏立 男,1966年生于山西运城.教授,博士生导师,研究方向为宽带移动卫星通信.阵列信号处理.
- 基金资助:
- 国家自然科学基金 (No.61179005）

Improved Adaptive Markov IMM Algorithm

DAI Ding-cheng¹, YAO Min-li¹, CAI Zong-ping², HE Heng¹

1. Department of Information Engineering, Rocket Force University of Engineering, Xi'an, Shaanxi 710025, China;
2. Department of Automation, Rocket Force University of Engineering, Xi'an, Shaanxi 710025, China

Received:2015-11-18 Revised:2016-03-01 Online:2017-05-25 Published:2017-05-25
- Supported by:
- National Natural Science Foundation of China (No.61179005)

摘要/Abstract

摘要：

针对机动目标跟踪问题，首先推导了马尔可夫参数自适应IFIMM算法自适应调节模型切换矩阵的必要条件，进一步分析了马尔可夫矩阵修正IMM跟踪算法的适用局限性.通过重新定义模型误差压缩率之比，提出了一种改进的马尔可夫参数自适应IMM算法，并阐述了误差压缩率之比的特性.最后进行了仿真实验并指出了马尔可夫自适应IMM算法的适用范围.

关键词: 目标跟踪, 交互式多模型, 马尔可夫矩阵, 后验信息

Abstract:

To solve the maneuvering target tracking problem,firstly,the essential condition of adaptive adjusting model based on adaptive Markov parameter IFIMM algorithm is deduced.Then the limitation of adaptive Markov parameter IMM algorithm is further analyzed.Through redefining the error compression ratio between models,an improved adaptive Markov parameter IMM algorithm is proposed,and the character of the error compression ratio is elaborated.Finally,application scope of improved adaptive Markov parameter IMM algorithm is delimited by simulation experiments.

Key words: target tracking, interacting multiple model(IMM), Markov matrix, posterior information

中图分类号:

TP391

戴定成, 姚敏立, 蔡宗平, 等. 改进的马尔可夫参数自适应IMM算法[J]. 电子学报, 2017, 45(5): 1198-1205.

DAI Ding-cheng, YAO Min-li, CAI Zong-ping, et al. Improved Adaptive Markov IMM Algorithm[J]. Acta Electronica Sinica, 2017, 45(5): 1198-1205.

参考文献

[1] Mazor E,Averbuch A,Bar-Shalom Y,et al.Interacting multiple model methods in target tracking: a survey[J].IEEE Trans on Aerospace and Electronic Systems,1998,34(1):103-123.
[2] Zhang L,Mao X.Vehicle density estimation of freeway traffic with unknown boundary demand-supply: an interacting multiple model approach[J].IET Control Theory & Applications,2015,9(13):1989-1995.
[3] Reali F,Palmerini G B,Farina A,et al.Parametric analysis of ballistic target-tracking problem by multiple model approach[J].IET Radar Sonar & Navigation,2013,7(4):459-469.
[4] Chen X L,Gao J,Han X.An algorithm based on interacting multiple models for maneuvering target tracking[A].Information Technology and Artificial Intelligence Conference (ITAIC)[C].IEEE,2014.405-408.
[5] Hou J,Li X R,Jing Z.Multiple model tracking of manoeuvring targets accounting for standoff jamming information[J].IET Radar Sonar & Navigation,2013,7(4):342-350.
[6] 蔡宗平,戴定成,牛创.基于容积粒子滤波的交互式多模型算法[J].系统工程与电子技术,2014,36(12):2366-2370. Cai Z P,Dai D C,Niu C.Interacting multiple model algorithm with cubature particle filter[J].Systems Engineering and Electronics,2014,36(12):2366-2370.(in Chinese)
[7] Lee S J,Motai Y,Choi H.Tracking Human Motion With Multichannel Interacting Multiple Model[J].IEEE Trans.on Industrial Informatics,2013,9(3):1751-1763.
[8] Jin B,Bo J,Su T,et al.Switched Kalman filter-interacting multiple model algorithm based on optimal autoregressive model for manoeuvring target tracking[J].IET Radar Sonar & Navigation,2015,9(2):199-209.
[9] Fu X,Shang Y,Yuan H.Improved diagonal interacting multiple model algorithm for manoeuvering target tracking based on H∞ filter[J].IET Control Theory & Applications,2015,9(12):1887-1892.
[10] Lan J,Li X R,Jilkov V P,et al.Second-Order Markov Chain Based Multiple-Model Algorithm for Maneuvering Target Tracking[J].IEEE Trans on Aerospace & Electronic Systems,2013,49(1):3-19.
[11] Wu P,Li X,Zhang L,et al.Tracking algorithm with radar and infrared sensors using a novel adaptive grid interacting multiple model[J].IET Science,Measurement & Technology,2014,8(5):270-276.
[12] Li W,Jia Y.An information theoretic approach to interacting multiple model estimation[J].IEEE Trans on Aerospace & Electronic Systems,2015,51(3):1811-1825.
[13] 臧荣春,崔平远.马尔可夫参数自适应IFIMM算法研究[J].电子学报,2006,34(3):521-524. Zang R C,Cui P Y.Research on adaptive Markov parameter IFIMM algorithm[J].Acta Electronica Sinica,2006,34(3):521-524.(in Chinese)
[14] 封普文,黄长强,曹林平,等.马尔可夫矩阵修正IMM跟踪算法[J].系统工程与电子技术,2013,35(11):2269-2274. Feng P W,Huang C Q,Cao L P,et al.Research on adaptive Markov matrix IMM tracking algorithm[J].Systems Engineering & Electronics,2013,35(11):2269-2274.(in Chinese)
[15] Qu H Q,Pang L P,Li S H.A novel interacting multiple model algorithm[J].Signal Processing,2009,89(11):2171-2177.tiple model approach[J][J].IET Control Theory & Applications, 2015, 9(13):1989-1995 [3]Reali F, Palmerini G B, Farina A, et al.Parametric analysis of ballistic target-tracking problem by multiple model approach[J].IET Radar Sonar & Navigation, 2013, 7(4):459-469 [4]Chen X L, Gao J, Han X.An algorithm based on interacting multiple models for maneuvering target tracking[C]// Information Technology and Artificial Intelligence Conference (ITAIC), 2014 IEEE 7th Joint International. IEEE, 2014:405-408.3 [5]Hou J, Li X R, Jing Z.Multiple model tracking of manoeuvring targets accounting for standoff jamming information[J].IET Radar Sonar & Navigation, 2013, 7(4):342-350 [6]蔡宗平, 戴定成, 牛创.基于容积粒子滤波的交互式多模型算法[J].系统工程与电子技术, 2014, 36(12):2366-2370 [7]Lee S J, Motai Y, Choi H.Tracking Human Motion With Multichannel Interacting Multiple Model[J].IEEE Trans. on Industrial Informatics, 2013, 9(3):1751-1763 [8]Jin B, Bo J, Su T, et al.Switched Kalman filter-interacting multiple model algorithm based on optimal autoregressive model for manoeuvring target tracking[J].IET Radar Sonar & Navigation, 2015, 9(2):199-209 [9]Fu X, Shang Y, Yuan H.Improved diagonal interacting multiple model algorithm for manoeuvering target tracking based on H∞ filter[J].IET Control Theory & Applications, 2015, 9(12):1887-1892 [10]Lan J, Li X R, Jilkov V P, et al.Second-Order Markov Chain Based Multiple-Model Algorithm for Maneuvering Target Tracking[J].IEEE Trans. on Aerospace & Electronic Systems, 2013, 49(1):3-19 [11]Wu P, Li X, Zhang L, et al.Tracking algorithm with radar and infrared sensors using a novel adaptive grid interacting multiple model[J].IET Science, Measurement & Technology, 2014, 8(5):270-276 [12]Li W, Jia Y.An information theoretic approach to interacting multiple model estimation[J].IEEE Trans. on Aerospace & Electronic Systems, 2015, 51(3):1811-1825 [13]臧荣春, 崔平远.马尔可夫参数自适应算法研究[J].电子学报, 2006, 03期(3):521-524 [14]封普文, 黄长强, 曹林平, 等.马尔可夫矩阵修正跟踪算法[J].系统工程与电子技术, 2013, 11期(11):2269-2274 [15]Qu H Q, Pang L P, Li S H.A novel interacting multiple model algorithm[J].Signal Processing, 2009, 89(11):2171-2177

改进的马尔可夫参数自适应IMM算法

Improved Adaptive Markov IMM Algorithm

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	李豪, 袁广林, 秦晓燕, 琚长瑞, 朱虹. 基于空间加权对数似然比相关滤波与Deep Snake的目标轮廓跟踪[J]. 电子学报, 2023, 51(1): 105-116.
[2]	谢青松, 刘晓庆, 安志勇, 李博. 基于前景优化的视觉目标跟踪算法[J]. 电子学报, 2022, 50(7): 1558-1566.
[3]	侯利明, 连峰, 谭顺成, 徐从安. 闪烁噪声统计特性未知情况下的鲁棒广义标签多伯努利滤波器[J]. 电子学报, 2021, 49(7): 1346-1353.
[4]	陈丹, 姚伯羽. 运动模型引导的自适应核相关目标跟踪方法[J]. 电子学报, 2021, 49(3): 550-558.
[5]	罗大鹏, 杜国庆, 曾志鹏, 魏龙生, 高常鑫, 陈应, 肖菲, 罗琛. 基于少量样本学习的多目标检测跟踪方法[J]. 电子学报, 2021, 49(1): 183-191.
[6]	马少雄, 邱实, 唐颖, 张晓. 基于工地场景的深度学习目标跟踪算法[J]. 电子学报, 2020, 48(9): 1665-1671.
[7]	田增山, 廉颖慧, 周牧, 李泽, 金悦. 基于Wi-Fi多维参数特征的无源目标跟踪技术[J]. 电子学报, 2020, 48(8): 1572-1579.
[8]	陈辉, 贺忠良, 邓东明, 李国财. 高斯混合多伯努利滤波器基于柯西施瓦兹散度的传感器控制方法[J]. 电子学报, 2020, 48(4): 706-716.
[9]	叶瑾, 许枫, 杨娟, 王佳维. 一种基于多传感器的复合量测IMM-EKF数据融合算法[J]. 电子学报, 2020, 48(12): 2326-2330.
[10]	王树亮, 毕大平, 阮怀林, 杜明洋, 潘继飞. 基于信息熵准则的认知雷达机动目标跟踪算法[J]. 电子学报, 2019, 47(6): 1277-1284.
[11]	陈辉, 贺忠良, 连峰, 黎慧波. 基于高斯混合多目标滤波器的传感器控制策略[J]. 电子学报, 2019, 47(3): 521-530.
[12]	李姝怡, 程婷. 基于量测转换IMM的多普勒雷达机动目标跟踪[J]. 电子学报, 2019, 47(3): 538-544.
[13]	张浩为, 谢军伟, 葛佳昂, 宗彬锋, 路文龙. 基于波形调度的机动目标跟踪算法[J]. 电子学报, 2019, 47(3): 560-567.
[14]	戴忠华, 周穗华, 张宏欣, 单珊. 初值自适应的磁性目标跟踪方法[J]. 电子学报, 2019, 47(12): 2457-2464.
[15]	查宇飞, 吴敏, 库涛, 陈兵, 张园强. 基于位置敏感模型的深度跟踪算法研究[J]. 电子学报, 2019, 47(10): 2076-2082.