地磁背景下基于传感器阵列的磁偶极子目标跟踪方法

陈路昭; 冯永强; 郭瑞杰; 朱万华; 方广有

doi:10.11999/JEIT190236

地磁背景下基于传感器阵列的磁偶极子目标跟踪方法

doi: 10.11999/JEIT190236

陈路昭^{1, 2, 3},
冯永强^{1, 2},
郭瑞杰³,
朱万华^1, ,,
方广有¹

1.
中国科学院电磁辐射与探测技术重点实验室北京 100190
2.
中国科学院大学北京 100049
3.
北京自动化控制设备研究所北京 100074

基金项目: 国家自然科学基金青年基金(41704177)和国家重点研发计划“深地资源勘查开采”重点专项(2018YFC0603201)

详细信息

作者简介:
陈路昭：男，1992年生，博士，研究方向为传感器阵列的磁信号处理方法、运动平台磁干扰补偿技术

冯永强：男，1985年生，博士生，研究方向为航磁系统硬件设计与航磁数据处理方法

郭瑞杰：女，1992年生，硕士，研究方向为组合导航与系统控制技术

朱万华：男，1982年生，副研究员，主要研究方向为高灵敏度磁场传感器关键技术、高性能磁屏蔽关键技术

方广有：男，1963年生，研究员，主要研究方向为超宽带电磁场理论及工程应用、超宽带雷达成像技术、微波成像新方法和新技术

通讯作者:
朱万华　whzhu@mail.ie.ac.cn

中图分类号: O411.5; TN911.73
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- 被引次数: 0
出版历程
- 收稿日期: 2019-04-10
- 修回日期: 2019-12-01
- 网络出版日期: 2019-12-09
- 刊出日期: 2020-03-19

Magnetic Dipole Object Tracking Algorithm Based on Magnetometer Array in Geomagnetic Background

Luzhao CHEN^{1, 2, 3},
Yongqiang FENG^{1, 2},
Ruijie GUO³,
Wanhua ZHU^{1
, ,},
Guangyou FANG¹

1.
Key Laboratory of Electromagnetic Radiation and Sensing Technology, Chinese Academy of Sciences, Beijing 100190, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China
3.
Beijing Automation Control Equipment Institute, Beijing 100074, China

Funds: The Youth Program of National Natural Science Foundation of China (41704177), The National Key R&D Program of China (2018YFC0603201)

摘要

摘要:
针对地磁背景下磁偶极子目标跟踪过程中存在的地磁干扰与模型非线性的问题，该文提出一种基于差量磁异常的蒙特卡洛卡尔曼滤波(MCKF)跟踪方法。新的跟踪方法以传感器阵列测量磁场的差量作为观测信号，并利用蒙特卡洛卡尔曼滤波算法解决模型的非线性问题，实现磁偶极子目标的实时跟踪。通过仿真跟踪实验，结果表明该文算法较传统的扩展或无迹卡尔曼滤波算法在稳定跟踪过程中对目标特征参数的估计更精确；通过地磁背景跟踪实验，结果验证了该文算法较传统算法在低信噪比下的性能优势。
- 磁偶极子 /
- 蒙特卡洛卡尔曼滤波 /
- 传感器阵列 /
- 地磁背景
Abstract:
In order to solve the problem of geomagnetic interference and model nonlinearity in the tracking process of magnetic dipole under geomagnetic background, Monte Carlo Kalman Filter (MCKF) tracking method based on differential magnetic anomaly is proposed in this paper. The new tracking method takes the difference of magnetic field measured by sensor array as the observation signal, and uses Monte Carlo Kalman Filtering (MCKF) algorithm to solve the nonlinear problem of the model to realize the real-time tracking of magnetic dipole targets. The simulation results show that the proposed method is more accurate than the traditional Extended Kalman Filter (EKF) or Untracked Kalman Filter (UKF) in the stable tracking process. The results of real geomagnetic background tracking experiments show that the proposed algorithm has better tracking performance under low SNR.
- Magnetic dipole /
- Monte Carlo Kalman Filter (MCKF) /
- Sensor array /
- Geomagnetic background

HTML全文

图 1 仿真磁偶极子运动轨迹与传感器分布位置

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图 2 传感器测量结果

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图 3 基于MCKF跟踪算法的流程图

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图 4 仿真磁偶极子跟踪结果对比

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图 5 真实目标跟踪实验

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图 6 跟踪实验模拟磁性目标体

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图 7 阵列传感器测量磁场与差量磁场

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图 8 模拟磁性目标的位置跟踪结果

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图 9 模拟磁性目标的磁矩跟踪结果

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表 1 不同跟踪算法各方向投影轨迹跟踪误差(m)

	跟踪算法	时间区间
	跟踪算法	1～40点	41～80点	81～120点	120～160点	160～200点
x方向	EKF	0.0651	0.0127	0.0023	0.0057	0.0409
	UKF	0.0689	0.0127	0.0024	0.0057	0.0410
	MCKF	0.2143	0.0153	0.0024	0.0039	0.0218
y方向	EKF	0.0491	0.0113	0.0059	0.0100	0.0319
	UKF	0.0512	0.0112	0.0061	0.0096	0.0318
	MCKF	0.1237	0.0115	0.0042	0.0061	0.0158
z方向	EKF	0.0430	0.0089	0.0021	0.0042	0.0163
	UKF	0.0436	0.0088	0.0022	0.0041	0.0164
	MCKF	0.0456	0.0086	0.0022	0.0043	0.0198

下载: 导出CSV

表 2 不同蒙特卡洛样本点数的算法各方向投影轨迹跟踪误差(m)

表2(a) x方向
蒙特卡洛样本点数	时间区间
蒙特卡洛样本点数	1～40	41～80	81～120	120～160	160～200
50	0.2817	0.0242	0.0035	0.0052	0.0264
100	0.2481	0.0194	0.0030	0.0046	0.0231
200	0.2143	0.0153	0.0024	0.0039	0.0218
400	0.2316	0.0159	0.0023	0.0039	0.0212
表2(b) y方向
蒙特卡洛样本点数	时间区间
蒙特卡洛样本点数	1～40	41～80	81～120	120～160	160～200
50	0.1658	0.0168	0.0049	0.0069	0.0192
100	0.1442	0.0141	0.0047	0.0063	0.0166
200	0.1237	0.0115	0.0042	0.0061	0.0158
400	0.1346	0.0118	0.0043	0.0059	0.0151
表2(c) z方向
蒙特卡洛样本点数	时间区间
蒙特卡洛样本点数	1～40	41～80	81～120	120～160	160～200
50	0.0569	0.0124	0.0031	0.0053	0.0242
100	0.0496	0.0105	0.0026	0.0046	0.0202
200	0.0456	0.0086	0.0022	0.0043	0.0198
400	0.0466	0.0090	0.0021	0.0042	0.0195

下载: 导出CSV

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