On Anti-outlier Localization for Integrated Long Baseline/Ultra-short Baseline Systems

Yan WANG; Qing LI; Guangpu ZHANG

doi:10.11999/JEIT180056

Volume 40 Issue 11

Oct. 2018

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(11): 2578-2583

Xiao Lei, Liang Qinglin. THE TECHNOLOGY TO REJECT MAI IN DS/CDMA SYSTEM[J]. Journal of Electronics & Information Technology, 2000, 22(2): 316-324.

Citation:

Yan WANG, Qing LI, Guangpu ZHANG. On Anti-outlier Localization for Integrated Long Baseline/Ultra-short Baseline Systems[J]. Journal of Electronics & Information Technology, 2018, 40(11): 2578-2583. doi: 10.11999/JEIT180056

Xiao Lei, Liang Qinglin. THE TECHNOLOGY TO REJECT MAI IN DS/CDMA SYSTEM[J]. Journal of Electronics & Information Technology, 2000, 22(2): 316-324.

Citation:

PDF( 952 KB)

On Anti-outlier Localization for Integrated Long Baseline/Ultra-short Baseline Systems

doi: 10.11999/JEIT180056

1.
Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China
2.
College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China

Funds: The National Natural Science Foundation of China (61405041), The National Key Research and Development Program (2017YFC0306900), The Technology Basic Research Program (JSJL2016604B003), The Qingdao National Laboratory for Marine Science and Technology Open Fund (QNLM2016ORP0102)

Received Date: 2018-01-16
Rev Recd Date: 2018-07-09

Available Online: 2018-07-18

Publish Date: 2018-11-01

Abstract

Abstract

Complicated underwater environment puts forward high requirements on the fault-tolerant and reliability of underwater acoustic localization systems. An anti-outlier localization method based on K-Means Clustering and Decision Fusion (KMCDF) is proposed for integrated Long baseline/Ultra-Short BaseLine (L/USBL) systems. Firstly, the target position is preliminarily estimated by the multi-parameter redundant information measured by the integrated system. Then, the clustering degree of the preliminary coordinates is analyzed by k-means clustering. According to the incompatibility between outliers and normal parameters, the outliers are identified by the decision fusion method. Furthermore, the impact of outliers on positioning is eliminated. Simulation analysis shows that the proposed method fully incorporates the multi-parameter information, and the tolerance of outliers is better than the existing anti-outlier positioning methods based on the time-delay parameter. Lake trial results demonstrate further the effectiveness of the proposed method.
- Reliable localization,
- Integrated baseline,
- Outlier,
- Clustering,
- Decision fusion

FullText(HTML)

References(16)

References

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

汝小虎, 柳征, 姜文利, 等. 带虚警抑制的基于归一化残差的野值检测方法[J]. 电子与信息学报, 2015, 37(12): 2898–2905 doi: 10.11999/JEIT150469

RU Xiaohu, LIU Zheng, JIANG Wenli, et al. Normalized residual-based outlier detection with false-alarm probability controlling[J].Journal of Electronics&Information Technology, 2015, 37(12): 2898–2905 doi: 10.11999/JEIT150469

庞菲菲, 张群飞, 史文涛, 等. 基于Parzen窗的水下无线传感器网络目标定位方法[J]. 电子与信息学报, 2017, 39(1): 45–50 doi: 10.11999/JEIT160246

PANG Feifei, ZHANG Qunfei, SHI Wentao, et al. Target localization method based on Parzen window in underwater wireless sensor network[J]. Journal of Electronics&Information Technology, 2017, 39(1): 45–50 doi: 10.11999/JEIT160246

LIU Donggang, NING Peng, and DU Wenliang Kevin. Attack-resistant location estimation in sensor networks[C]. Proceedings of the 4th International Symposium on Information Processing in Sensor Networks, Los Angeles, USA, 2005: 99–106.

LIU Donggang, NING Peng, LIU An, et al. Attack-resistant location estimation in wireless sensor networks[J]. ACM Transactions on Information and System Security, 2008, 11(4): 1–39 doi: 10.1145/1380564.1380570

LI Zang, TRAPPE W, ZHANG Yanyong, et al. Robust statistical methods for securing wireless localization in sensor networks[C]. Proceedings of the 4th International Symposium on Information Processing in Sensor Networks, Los Angeles, USA, 2005: 91–98.

KORKMAZ S and VEEN A J V D. Robust localization in sensor networks with iterative majorization techniques[C]. Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, Taipei, China, 2009: 2049–2052.

张天骐, 杨强, 宋玉龙, 等. 一种K-means改进算法的软扩频信号伪码序列盲估计[J]. 电子与信息学报, 2018, 40(1): 226–234 doi: 10.11999/JEIT170306

ZHANG Tianqi, YANG Qiang, SONG Yulong, et al. Blind estimation PN sequence in soft spread spectrum signal of improved k-means algorithm[J]. Journal of Electronics&Information Technology, 2018, 40(1): 226–234 doi: 10.11999/JEIT170306

朱明. 数据挖掘[M]. 合肥: 中国科技大学出版社, 2002: 22, 139–157.

ZHU Ming. Data Mining[M]. Hefei: University of Science and Technology of China Press, 2002: 22, 139–157.

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

王燕, 岳剑平, 冯海泓. 双基阵纯方位目标运动分析研究[J]. 声学学报, 2001, 26(5): 405–409 doi: 10.15949/j.cnki.0371-0025.2001.05.005

WANG Yan, YUE Jianping, and FENG Haihong. Study on bearings-only target motion analysis based on association of dual arrays[J]. Acta Acustica, 2001, 26(5): 405–409 doi: 10.15949/j.cnki.0371-0025.2001.05.005

付进. 长基线定位信号处理若干关键技术研究[D]. [博士论文], 哈尔滨工程大学, 2007.

FU Jin. Research on several key techniques of the signal processing for long baseline location[D]. [Ph.D. dissertation], Harbin Engineering University, 2007.

张捍东, 孙成慧, 岑豫皖. 分布式多传感器结构中的数据融合方法[J]. 华中科技大学学报, 2008, 36(6): 37–39 doi: 10.13245/j.hust.2008.06.036

ZHANG Handong, SUN Chenghui, and CEN Yuwan. Data fusion method for the configuration of distributed multi-sensor[J]. Journal of Huazhong University of Science and Technology, 2008, 36(6): 37–39 doi: 10.13245/j.hust.2008.06.036

蒋正新, 施国梁. 矩阵理论及其应用[M]. 北京: 北京航空学院出版社, 1988: 371–378.

JIANG Zhengxin and SHI Guoliang. Matrix Theory and Application[M]. Beijing: Beihang University Press, 1988: 371–378.

梁继民. 多传感器决策融合方法研究[D]. [博士论文], 西安电子科技大学, 1999.

LIANG Jimin. Study of multisensor decision fusion[D]. [Ph.D. dissertation], Xidian University, 1999.

Relative Articles

Supplements(0)

Cited By

Proportional views