基于三角稳定的海上目标航迹抗差关联算法

doi:10.3969/j.issn.1001-506X.2020.10.10

Abstract

Abstract:

Aiming at the problems of the existing track anti-bias association algorithms lack the consideration of the characteristics and principal of the marine target track and the poor practical application effect, according to the comparative analysis results of typical measured data, combined with the characteristics of slow change of marine target position and stable spatial topology association, and based on the triangle stable structure, the anti-bias association algorithm for marine target track is designed. Firstly, the topological triangle is constructed, and the threshold is determined by the triangle matching coefficient and the track map matching coefficient, and the correlation coefficient of the track pair is obtained. Secondly, the maximum correlation coefficient is retained and the track pair correlation coefficient matrix is constructed. Finally, the maximum correlation coefficient and threshold discrimination principle are used to output the associated track. The experimental results show that the proposed algorithm achieves the effective correlation of all tracks, which is obviously better than the comparison algorithms, and has strong stability and robustness. It can effectively solve the problem of track association of maritime targets in practice, and has strong practicability.

Key words: marine target, track association, triangular stability, radar network

CLC Number:

TN953
TN957

Yaqi CUI, Wei XIONG, Xiangqi GU. Anti-bias association algorithm for marine target track based on triangular stability[J]. Systems Engineering and Electronics, 2020, 42(10): 2223-2230.

Figures/Tables 11

Fig.1

Fig.2

Table 1

Table 2

Fig.3

Table 3

Table 4

Fig.4

Fig.5

Table 5

Table 6

References 31

1	何友, 王国宏, 关欣. 信息融合理论及应用[M]. 北京: 电子工业出版社, 2010.
	HE Y , WANG G H , GUAN X . Information fusion theory and applications[M]. Beijing: Publishing House of Electronics Industry, 2010.
2	齐林, 王海鹏, 熊伟, 等. 基于先验信息的多假设模型中断航迹关联算法[J]. 系统工程与电子技术, 2015, 37 (4): 732- 739.
	QI L , WANG H P , XIONG W , et al. Track segment association algorithm based on multiple hypothesis models with priori information[J]. Systems Engineering and Electronics, 2015, 37 (4): 732- 739.
3	TESTA L A, PICKLE C D, BLACKMAN S S. A dempster-shafer approach to multi-sensor track association[C]//Proc.of the IEEE Aerospace Conference, 2016.
4	YANG M , WU Y W , JIA Y D . A hybrid data association framework for robust online multi-object tracking[J]. IEEE Trans.on Image Processing, 2017, 26 (12): 5667- 5679. doi: 10.1109/TIP.2017.2745103
5	刘根旺, 刘永信, 纪永刚, 等. 基于模糊双门限的高频地波雷达与AIS目标航迹关联方法[J]. 系统工程与电子技术, 2016, 38 (3): 557- 562.
	LIU G W , LIU Y X , JI Y G , et al. Track association for high-frequency surface wave radar and AIS based on fuzzy double threshold theory[J]. Systems Engineering and Electronics, 2016, 38 (3): 557- 562.
6	袁天, 陶建锋, 李兴成. 基于关联准则的主辫航迹欺骗干扰方法[J]. 系统工程与电子技术, 2018, 40 (2): 273- 279.
	YUAN T , TAO J F , LI X C . Main lobe track deception jamming method based on association rule[J]. Systems Engineering and Electronics, 2018, 40 (2): 273- 279.
7	TIAN W , WANG Y , SHAN X M , et al. Analytic performance prediction of track-to-track association with biased data in multi-sensor multi-target tracking scenarios[J]. Sensors, 2013, 13 (9): 12244- 12265. doi: 10.3390/s130912244
8	HE X X , WANG T , LIU W , et al. Measurement data fusion based on optimized weighted least-squares algorithm for multi-target track-ing[J]. IEEE Access, 2019, 7, 13901- 13916. doi: 10.1109/ACCESS.2019.2894641
9	XU Z J, LI J C, CHEN Y F. Survey of track association of radar and AIS[C]//Proc.of the 2nd International Conference on Ima-ge, Vision and Computing, 2017.
10	ZHANG X Y , TAN S C . Effect of biased estimation on radar-to-ESM, track association[J]. Journal of Systems Engineering and Electronics, 2012, 23 (2): 188- 194. doi: 10.1109/JSEE.2012.00024
11	ZHU H , WANG M L , YUEN K V , et al. Track-to-track association by coherent point drift[J]. IEEE Signal Processing Letters, 2017, 24 (5): 634- 647.
12	ZHU H Y , WANG W , WANG C . Robust track-to-track association in the presence of sensor biases and missed detections[J]. Information Fusion, 2016, 27, 33- 40. doi: 10.1016/j.inffus.2015.05.002
13	LI P, GE H W, WANG W H. Track association for B-spline Gaussian mixture PHD filter using shape information[C]//Proc.of the 3rd Information Technology & Mechatronics Engineering Conference, 2017.
14	ZHANG Y J , LEI M . PHD track association algorithm based on measurement partition[J]. Journal of Harbin Institute of Technology, 2018, 50 (4): 62- 70.
15	SHENG H , ZHANG Y , CHEN J H , et al. Heterogeneous association graph fusion for target association in multiple object tracking[J]. IEEE Trans.on Circuits and Systems for Video Technology, 2019, 29 (11): 3269- 3280. doi: 10.1109/TCSVT.2018.2882192
16	LI X, HE C L, WU W, et al. An adaptive technique for track association against large bias[C]//Proc.of the 7th International Symposium on Computational Intelligence & Design, 2015.
17	李保珠, 董云龙, 李秀友, 等. 基于t分布混合模型的抗差关联算法[J]. 电子与信息学报, 2017, 39 (7): 1774- 1778.
	LI B Z , DONG Y L , LI X Y , et al. Anti-bias track association algorithm based on t-distribution mixture model[J]. Journal of Electronics & Information Technology, 2017, 39 (7): 1774- 1778.
18	GENG W D, WANG Y Q, DONG Z H. Single-group-target data association and track maintenance[M]//Group-target Tracking. Singapore: Springer, 2017: 85-98.
19	杨哲, 韩崇昭, 李晨, 等. 基于目标之间拓扑信息的数据关联方法[J]. 系统仿真学报, 2008, 20 (9): 2357- 2360.
	YANG Z , HAN C Z , LI C , et al. Data association based on target topology[J]. Journal of System Simulation, 2008, 20 (9): 2357- 2360.
20	齐林, 熊伟, 何友. 基于距离分级聚类的机载雷达航迹抗差关联算法[J]. 电子学报, 2018, 46 (6): 198- 204.
	QI L , XIONG W , HE Y . Anti-bias track association algorithm for aircraft platforms based on distance hierarchical clustering[J]. Acta Electronica Sinica, 2018, 46 (6): 198- 204.
21	QI L , DONG K , LIU Y , et al. Anti-bias track-to-track associa-tion algorithm based on distance detection[J]. IET Radar, Sonar & Navigation, 2017, 11 (2): 269- 276.
22	QI L , HE Y , DONG K , et al. Multi-radar anti-bias track association based on the reference topology feature[J]. IET Radar, Sonar & Navigation, 2018, 12 (3): 366- 372.
23	齐林, 刘瑜, 任华龙, 等. 空基多雷达航迹抗差关联算法[J]. 航空学报, 2018, 39 (3): 321691-1- 321691-9.
	QI L , LIU Y , REN H L , et al. Air-platform multi-radar anti-bias tracks association algorithm[J]. Acta Aeronautica Et Astronautica Sinica, 2018, 39 (3): 321691-1- 321691-9.
24	ZHU H , LEUNG H , YUEN K V . A joint data association, registration, and fusion approach for distributed tracking[J]. Information Sciences, 2015, 324, 186- 196. doi: 10.1016/j.ins.2015.06.042
25	TOKTA A, HOCAOGLU A K. A fast track to track association algorithm by sequence processing of target states[C]//Proc.of the 21st International Conference on Information Fusion, 2018.
26	ZHU H Y , WANG C . Joint track-to-track association and sensor registration at the track level[J]. Digital Signal Processing, 2015, 41, 48- 59. doi: 10.1016/j.dsp.2015.03.012
27	YUAN T , KRISHNAN K , CHEN Q , et al. Object matching for inter-vehicle communication systems-an IMM-based track association approach with sequential multiple hypothesis test[J]. IEEE Trans.on Intelligent Transportation Systems, 2017, 18 (12): 3501- 3512. doi: 10.1109/TITS.2017.2723894
28	WANG K D, GE Y. Real-time flight test track filtering and association using Kalman filter and QDA classifier[C]//Proc.of the International Conference on Intelligent Autonomous Systems, 2017: 675-685.
29	XIE Y F , HUANG Y , SONG T L . Iterative joint integrated probabilistic data association filter for multiple-detection multiple-target tracking[J]. Digital Signal Processing, 2017, 72, 232- 243.
30	CHONG C Y , MORI S , BARKER W H , et al. Architectures and algorithms for track association and fusion[J]. IEEE Aerospace and Electronic Systems Magazine, 2000, 15 (1): 5- 13. doi: 10.1109/62.821657
31	MORI S , BARKER W , CHONG C Y , et al. Track association and track fusion with nondeterministic target dynamics[J]. IEEE Trans.on Aerospace & Electronic Systems, 2002, 38 (2): 659- 668.

参数	关联对(雷达1-雷达2)
参数	15-25	13-23	11-21	12-22
X平移误差估计/m	512.14	512.14	512.14	515.75
Y平移误差估计/m	807.71	807.71	807.71	810.12
旋转误差估计/(°)	0.784	0.784	0.784	0.723

参数	关联对(雷达1-雷达2)
参数	15-25	13-23	11-21	12-22
X平移误差估计/m	534.67	542.81	558.72	566.57
Y平移误差估计/m	868.24	878.50	878.95	884.71
旋转误差估计/(°)	0.751	0.719	0.707	0.683

参数	关联对(雷达1-雷达2)
参数	13-23	15-25	14-24	12-22
X平移误差估计/m	1 476.4	1 476.4	1 476.4	1 453.3
Y平移误差估计/m	2 353.4	2 353.4	2 353.4	2 336.3
旋转误差估计/(°)	2.4	2.4	2.4	2.3

参数	关联对(雷达1-雷达2)
参数	13-23	14-24
X平移误差估计/m	1 248.3	1 264.0
Y平移误差估计/m	2 281.1	2 291.7
旋转误差估计/(°)	2.1	2.0

[1]	Xin GUAN, Jia'en GUO. Anti-bias track association algorithm based on sequential detection of iterative discrete degree [J]. Systems Engineering and Electronics, 2022, 44(8): 2498-2505.
[2]	Hongliang LIU, Chao CHEN, Kunwei HUANG, Bo LU, Kai YUE. Multi-frame joint track initiation method for distributed radar network [J]. Systems Engineering and Electronics, 2022, 44(7): 2143-2147.
[3]	Xiao YI, Rui ZENG, Xinying CAO. Asynchronous anti-bias track association algorithm by using k-nearest neighbors interval distance [J]. Systems Engineering and Electronics, 2022, 44(5): 1475-1482.
[4]	Xiao YI, Rui ZENG. Asynchronous track-to-track association algorithm based on k means distance of nearest neighbors [J]. Systems Engineering and Electronics, 2022, 44(11): 3515-3521.
[5]	Xiao YI, Jinpeng DU, Xinying CAO. Asynchronous track association of radar and electronic support measurements at different sites [J]. Systems Engineering and Electronics, 2021, 43(4): 954-960.
[6]	Xin DU, Wei LIU, Yingfei SUN. Distributed network detection for low-altitude targets [J]. Systems Engineering and Electronics, 2020, 42(5): 1057-1062.
[7]	ZHANG Chao, JIN Peng, CHEN Jinyong, LI Yanbin, MA Wanquan. Virtual constellation task planning technology for emergency observation [J]. Systems Engineering and Electronics, 2019, 41(4): 819-825.
[8]	LIU Xiang, LI Dongsheng. Deviation compensation for phantom tracks jamming against distributed radar network [J]. Systems Engineering and Electronics, 2018, 40(6): 1255-1264.
[9]	FANG Min, CHENG Ziyang, HE Zishu, LI Jun. Multi-target paring algorithm for distributed radar with INS error [J]. Systems Engineering and Electronics, 2018, 40(2): 308-313.
[10]	WANG Guohong, JI Zhe. Multi-range-false-target jamming for radar network based on#br# multiple discriminations [J]. Systems Engineering and Electronics, 2017, 39(1): 40-48.
[11]	HU Xiao-wei, TONG Ning-ning, HE Xing-yu, LEI Teng, WANG Yu-chen. High-speed spinning target imaging based on narrow-band radar networks [J]. Systems Engineering and Electronics, 2016, 38(4): 792-798.
[12]	LIU Gen wang1,2, LIU Yong xin1, JI Yong gang2,3, WANG Chao2. Track association for highfrequency surface wave radar and AISbased on fuzzy double threshold theory [J]. Systems Engineering and Electronics, 2016, 38(3): 557-562.
[13]	HU Xiao-wei, TONG Ning-ning, WANG Jian-ye, DING Shan-shan, ZHAO Xiao-ru. Three-dimensional reconstruction for spatial precession targets with rotational symmetry in radar networks [J]. Systems Engineering and Electronics, 2016, 38(10): 2281-2286.
[14]	LI Yang, ZHANG Jing. Real-time error registration algorithm and analysis#br# based on the SINGER model [J]. Systems Engineering and Electronics, 2015, 37(6): 1255-1258.
[15]	WU Jian-ping, WANG Guo-hong, SUN Dian-xing, GUAN Cheng-bin. Phantom track discrimination based on inspection of innovation in distributed radar network [J]. Systems Engineering and Electronics, 2015, 37(1): 67-72.

Anti-bias association algorithm for marine target track based on triangular stability

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 11

References 31

Related Articles 15

Recommended Articles

Metrics

Comments

雷达	关联对
1	17	12	11	18	14	13	16	15
2	27	22	21	28	24	23	26	25

雷达	关联对
1	17	12	11	18	14
2	27	22	21	28	24