超短基线定位系统融合分类解模糊技术研究

王燕; 李晴; 付进; 梁国龙

doi:10.11999/JEIT160825

超短基线定位系统融合分类解模糊技术研究

doi: 10.11999/JEIT160825

基金项目:

国家自然科学基金(51279043, 11504064, 61405041)，黑龙江省博士后科研启动金(LBH-Q15025)，技术基础科研项目(JSJL2016604B003)，黑龙江省留学归国人员科学基金(JJ2016LX 0051)

计量
- 文章访问数: 1287
- HTML全文浏览量: 140
- PDF下载量: 302
- 被引次数: 0
出版历程
- 收稿日期: 2016-08-03
- 修回日期: 2017-02-08
- 刊出日期: 2017-06-19

Resolving Ambiguity Using Fusion Classification for Ultra-short Baseline Positioning Systems

Funds:

The National Natural Science Foundation of China (51279043, 11504064, 61405041), The Postdoctoral Scientific Research Foundation of Heilongjiang Province (LBH-Q15025), The Technical Basic Research Project (JSJL2016604B003), The Science Foundation for the Returned Overseas Scholars of Heilongjiang Province, China (JJ2016LX0051)

摘要

摘要: 针对超短基线水声定位系统面临的相位差模糊问题，该文提出一种基于多分类器融合的定位解模糊算法。首先构建多分类器系统，将解模糊问题转化为对模糊数进行分类识别的问题，并采用Choquet积分对各分类器结果进行融合，得到模糊数所属类别，进而对目标进行定位。给出了目标位置的无模糊观测条件。该算法优点是无需构造小于半波长间距的阵列，有效扩大了无模糊阵列孔径，而且由于充分利用了相位差观测数据的统计特性，定位精度可接近克拉美-罗界。仿真结果验证了该算法的有效性。
- 超短基线定位 /
- 相位差模糊 /
- 多分类器融合 /
- 模糊积分
Abstract: To solve the phase-difference ambiguity problem in Ultra-Short BaseLine (USBL) underwater acoustic positioning systems, an ambiguity resolution and localization method based on Multiple Classifier Fusion (MCF) is proposed. Firstly, the multiple classifier system is built. Then, ambiguity resolution problem is formulated as classifying and recognizing the ambiguity integer, and Choquet integral is utilized for fusing the results of multiple classifiers. Finally, the category of ambiguity integer is obtained and the target is located. The unambiguous observation condition of the target position is derived. Without constructing an inter-sensor spacing less than half the wavelength, unambiguous aperture of the array is effectively enlarged. Moreover, as statistical characteristics of the observation data are fully utilized, the positioning accuracy approaches the Cramer-Rao bound. Simulation results verify the effectiveness of the proposed method.
- Ultra-Short BaseLine (USBL) positioning /
- Phase-difference ambiguity /
- Multiple Classifier Fusion (MCF) /
- Fuzzy integral

HTML全文

参考文献(29)

BAYAT M, CRASTA N, AGUIAR A P, et al. Range-based underwater vehicle localization in the presence of unknown ocean currents: Theory and experiments[J]. IEEE Transactions on Control Systems Technology, 2016, 24(1): 122-139. doi: 10.1109/TCST.2015.2420636.

RAMEZANI H, FAZEL F, STOJANOVIC M, et al. Collision tolerant and collision free packet scheduling for underwater acoustic localization[J]. IEEE Transactions on Wireless Communications, 2015, 14 (5): 2584-2595. doi: 10.1109/ TWC.2015.2389220.

韩云峰, 李昭, 郑翠娥, 等. 一种基于长基线交汇的超短基线定位系统精度评价方法[J]. 物理学报, 2015, 64(9): 094301. doi: 10.7498/aps.64.094301.

HAN Yunfeng, LI Zhao, ZHENG Cuie, et al. A precision evaluation method of USBL positioning systems based on LBL triangulation[J]. Acta Physica Sinica, 2015, 64(9): 094301. doi: 10.7498/aps.64.094301.

喻敏. 长程超短基线定位系统研制[D]. [博士论文], 哈尔滨工程大学, 2006.

YU Min. Research on long range ultra-short baseline system[D]. [Ph.D. dissertation], Harbin Engineering University, 2006.

张敏, 郭福成, 周一宇, 等. 时变长基线2维干涉仪测向方法[J]. 电子与信息学报,　2013, 35(12): 2882-2888. doi: 10.3724 /SP.J.1146.2013.00360.

ZHANG Min, GUO Fucheng, ZHOU Yiyu, et al. Direction finding method for two-dimension interferometer using the time varying long baseline[J]. Journal of Electronics Information Technology, 2013, 35(12): 2882-2888. doi: 10.3724/SP.J.1146.2013.00360.

LIU Zhangmeng and GUO Fucheng. Azimuth and elevation estimation with rotating long-baseline interferometers[J]. IEEE Transactions on Signal Processing, 2015, 63(9): 2405-2419. doi: 10.1109/TSP.2015.2405506.

周亚强, 皇甫堪. 噪扰条件下数字式多基线相位干涉仪解模糊问题[J]. 通信学报, 2005, 26(8): 16-21.

ZHOU Yaqiang and HUANGFU Kan. Solving ambiguity problem of digitized multi-baseline interferometer under noisy circumstance[J]. Journal on Communications, 2005, 26(8): 16-21.

龚享铱, 皇甫堪, 袁俊泉. 基于相位干涉仪阵列二次相位差的波达角估计算法研究[J]. 电子学报, 2005, 33(3): 444-446.

GONG Xiangyi, HUANGFU Kan, and YUAN Junquan. A new algorithm for estimation of direction of arrival based on the second-order difference of phase of interferometer array[J]. Acta Electronica Sinica, 2005, 33(3): 444-446.

LY P Q C, ELTON S D, GRAY D A, et al. Unambiguous AOA estimation using SODA interferometry for electronic surveillance[C], Proceedings of the IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, Hoboken, NJ, USA, 2012: 277-280.

龚享铱, 袁俊泉, 苏令华. 基于相位干涉仪阵列多组解模糊的波达角估计算法研究[J]. 电子与信息学报, 2006, 28(1): 55-59.

GONG Xiangyi, YUAN Junquan, and SU Linghua. A multi-pare unwrap ambiguity of interferometer array for estimation of direction of arrival[J]. Journal of Electronics Information Technology, 2006, 28(1): 55-59.

狄慧, 刘渝, 杨健, 等. 联合到达时间估计的长基线测向相位解模糊算法研究[J]. 电子学报, 2013, 41(3): 496-501. doi: 10.3969/j.issn.0372-2112.2013.03.013.

DI Hui, LIU Yu, YANG Jian, et al. Long baseline direction finding unwrapping phase ambiguity algorithm with TOA estimation[J]. Acta Electronica Sinica, 2013, 41(3): 496-501. doi: 10.3969/j.issn.0372-2112.2013.03.013.

魏合文, 王军, 叶尚福. 一种基于余弦函数的相位干涉仪阵列DOA估计算法[J]. 电子与信息学报,　2007, 29(11): 2665-2668.

WEI Hewen, WANG Jun, and YE Shangfu. An algorithm of estimation direction of arrival for phase interferometer array using cosine function[J]. Journal of Electronics Information Technology, 2007, 29(11): 2665-2668.

王熙照. 模糊测度和模糊积分及在分类技术中的应用[M]. 北京: 科学出版社, 2008: 18-25, 195-199.

WANG Xizhao. Fuzzy Measure and Fuzzy Integral and the Applications in Classification Technology[M]. Beijing: Science Press, 2008: 18-25, 195-199.

孔志周. 多分类器系统中信息融合方法研究[D]. [博士论文], 中南大学, 2011.

KONG Zhizhou. Study of information fusion methods in multiple classifier system[D]. [Ph.D. dissertation], Central South University, 2011.

SUGENO M. A way to Choquet calculus[J]. IEEE Transactions on Fuzzy Systems, 2015, 23 (5): 1439-1457. doi: 10.1109/TFUZZ.2014.2362148.

HAVENS T C, ANDERSON D T, and WAGNER C. Data-informed fuzzy measures for fuzzy integration of intervals and fuzzy numbers[J]. IEEE Transactions on Fuzzy Systems, 2015, 23(5): 1861-1875. doi: 10.1109/TFUZZ.2014. 2382133.

KAY S M. Fundamentals of Statistical Signal Processing: Estimation Theory[M]. New Jersey: Prentice Hall, 1993: 185-186.

曾勇. 广义近邻模式分类研究[D]. [博士论文], 上海交通大学, 2009.

ZENG Yong. Study on generalized nearest neighbor pattern classification[D]. [Ph.D. dissertation], Shanghai Jiao Tong University, 2009.

施引文献

资源附件(0)

访问统计

计量

文章访问数: 1287
HTML全文浏览量: 140
PDF下载量: 302
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

留言板

超短基线定位系统融合分类解模糊技术研究

doi: 10.11999/JEIT160825

计量

Resolving Ambiguity Using Fusion Classification for Ultra-short Baseline Positioning Systems

计量

目录

留言板

超短基线定位系统融合分类解模糊技术研究

doi: 10.11999/JEIT160825

计量

出版历程

Resolving Ambiguity Using Fusion Classification for Ultra-short Baseline Positioning Systems

计量

出版历程

目录