基于改進蓋爾-沙普利算法的自動識別系統(tǒng)與雙頻地波雷達斷裂航跡關聯(lián)

張暉; 曾顯普; 高亮

doi:10.11999/JEIT220005

基于改進蓋爾-沙普利算法的自動識別系統(tǒng)與雙頻地波雷達斷裂航跡關聯(lián)

doi: 10.11999/JEIT220005 cstr: 32379.14.JEIT220005

內蒙古大學電子信息工程學院呼和浩特 010021

基金項目: 國家重點研發(fā)計劃(2017YFC1405200)，國家自然科學基金(61701263)

詳細信息

作者簡介:
張暉：男，副教授，研究方向為智能信息處理、多傳感數(shù)據(jù)融合等

曾顯普：男，碩士生，研究方向為高頻地波雷達多目標跟蹤與航跡關聯(lián)

高亮：男，碩士生，研究方向為高頻地波雷達信號處理與仿真

通訊作者:
張暉　Hui.zhang@imu.edu.cn

中圖分類號: TN958
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2022-01-05
- 修回日期: 2022-08-31
- 網(wǎng)絡出版日期: 2022-09-02
- 刊出日期: 2023-03-10

Track Segment Association of Automatic Identification System and Dual-frequency High-Frequency Surface Wave Radar Based on Improved Gale-Shapley Algorithm

College of Electronic Information Engineering, Inner Mongolia University, Hohhot 010021, China

Funds: The National Key Research and Development Program of China (2017YFC1405200), The National Natural Science Foundation of China (61701263)

摘要

摘要: 高頻地波雷達(HFSWR)可以實現(xiàn)大范圍海上船只目標的連續(xù)探測，但是海雜波等干擾因素的影響容易造成跟蹤航跡的斷裂。目前關于地波雷達航跡關聯(lián)的研究中，通常忽略了航跡斷裂的情況，將航跡關聯(lián)視為二分圖匹配問題，這會導致可能將單一目標的斷裂航跡判斷為多個目標，從而引起目標的誤關聯(lián)。針對上述情況，該文結合模糊綜合評判和迭代搜索算法，首次將蓋爾-沙普利(GS)算法引入航跡關聯(lián)領域，并且對其進行改進以滿足航跡斷裂時的多對多航跡關聯(lián)情況，提出了改進的蓋爾-沙普利(IGS)算法。在該算法中，通過計算航跡之間的模糊綜合評判值來得到航跡之間的傾向度序列，再由迭代搜索對航跡進行聚類以獲得航跡集群，最后將航跡集群及傾向度序列輸入蓋爾-沙普利算法來進行數(shù)輪博弈以給出關聯(lián)結果。利用雙頻率高頻地波雷達和船只自動識別系統(tǒng)(AIS)的仿真數(shù)據(jù)與實測數(shù)據(jù)進行實驗測試，實驗結果表明：所提出的算法解決了在航跡斷裂情況下的多傳感器航跡關聯(lián)問題，且在密集區(qū)域的航跡關聯(lián)效果優(yōu)于傳統(tǒng)算法。
- 航跡關聯(lián) /
- 高頻地波雷達 /
- 航跡斷裂 /
- 蓋爾-沙普利算法
Abstract: Large-range maritime vessel targets can be detected continuously by High-Frequency Surface Wave Radar (HFSWR), but the tracking trajectory of the target is easily broken in the presence of disturbing factors such as sea clutter. In current studies on HFSWR track association, the case of broken tracks is usually ignored and the track association is considered as a bipartite graph matching problem, which can lead to the possibility of judging broken tracks of a single target as multiple targets, and thus wrong target association results are obtained. For the above situation, fuzzy integrated evaluation and iterative search algorithms are considered in this paper. The Gale-Shapley (GS) algorithm is introduced into the field of track association for the first time, and it is improved to satisfy the many-to-many track association case when the track is broken , the Improved Gale-Shapley (IGS) algorithm is proposed. In this algorithm, the tendency sequences between the tracks can be obtained by calculating the fuzzy composite judgment values between the tracks. Then, the tracks are clustered by an iterative search method to obtain the track clusters. Finally, the track clusters and the propensity sequences are fed into the Gale-Shapley algorithm to perform several rounds of games to give the association results. The measured data and simulation data of dual-frequency HFSWR and Automatic Identification System (AIS) are used for experimental tests. Experimental tests are conducted using simulated and measured data from dual-frequency HFSWR and AIS. The experimental results show that the multi-sensor track association problem in the case of track break can be solved by the proposed algorithm, and the track association effect in dense areas is better than that of the conventional algorithm.
- Track association /
- High-Frequency Surface Wave Radar(HFSWR) /
- Track breakage /
- Gale-Shapley (GS) algorithm

HTML全文

圖 1 航跡斷裂時的關聯(lián)情況示意圖

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圖 2 時間沖突時的決策流程圖

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圖 3 AIS和HFSWR仿真數(shù)據(jù)航跡關聯(lián)結果

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圖 4 AIS和HFSWR實測數(shù)據(jù)航跡關聯(lián)結果

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圖 5 AIS和HFSWR仿真數(shù)據(jù)局部航跡關聯(lián)結果

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圖 6 AIS和HFSWR雙頻航跡關聯(lián)結果

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圖 7 非合作目標航跡關聯(lián)結果

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表 1 航跡集G1詳細情況

航跡標號	傾向度表(正序)	航跡所屬時間(min)
A1	B1, B3, B2	03～19
A2	B3, B1, B2	30～43
A3	B3, B2, B1	23～46
A4	B1, B2, B3	21～49
B1	A2, A3, A4, A1	06～30
B2	A3, A4, A1, A2	12～36
B3	A3, A4, A2, A1	15～51

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表 2 航跡集G1匹配過程

邀約輪數(shù)	該輪邀約結束時的匹配結果
第1輪	A1-B1; A2-無 A3-B3; A4-B1
第2輪	A1-無; A2-B1; A3-B3; A4-無
第3輪	A1-B2; A2-B1; A3-B3; A4-B2

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表 3 航跡關聯(lián)結果性能分析

實驗數(shù)據(jù)和所用算法	關聯(lián)比例(%)	關聯(lián)正確率(%)	距離RMSE(km)	方位RMSE(°)	速度RMSE(km/h)	計算耗時(s)
仿真數(shù)據(jù)GNNDA	48.20	88.81	0.4077	0.2759	0.4401	5.73
仿真數(shù)據(jù)IGS	75.18	97.13	0.3863	0.2406	0.3826	11.82
實測數(shù)據(jù)GNNDA	42.06	未知	1.9930	1.8935	0.5024	6.49
實測數(shù)據(jù)IGS	60.75	未知	1.8783	1.6710	0.3438	13.05

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表 4 實測數(shù)據(jù)非合作目標雙頻航跡關聯(lián)個例分析(km/h)

航跡名	航跡時間	k1點速度	k2點速度	k3點速度	k4點速度	k5點速度	k6點速度
F1T1	09:57～10:22	–13.48	–12.26	–12.86	–13.33	無數(shù)值	無數(shù)值
F1T2	10:31～10:46	無數(shù)值	無數(shù)值	無數(shù)值	無數(shù)值	–13.23	–13.02
F2T1	09:57～10:12	–13.31	–12.48	無數(shù)值	無數(shù)值	無數(shù)值	無數(shù)值
F2T2	10:18～10:46	無數(shù)值	無數(shù)值	–12.43	–13.05	–13.01	–12.78

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參考文獻(14)

[1]	JI Yonggang, ZHANG Jie, MENG Junmin, et al. Point association analysis of vessel target detection with SAR, HFSWR and AIS[J]. Acta Oceanologica Sinica, 2014, 33(9): 73–81. doi: 10.1007/s13131-014-0498-2
[2]	劉根旺, 劉永信, 紀永剛, 等. 基于模糊雙門限的高頻地波雷達與AIS目標航跡關聯(lián)方法[J]. 系統(tǒng)工程與電子技術, 2016, 38(3): 557–562. doi: 10.3969/j.issn.1001-506X.2016.03.13 LIU Genwang, LIU Yongxin, JI Yonggang, 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. doi: 10.3969/j.issn.1001-506X.2016.03.13
[3]	SUN Weifeng, HUANG Weimin, JI Yonggang, et al. A vessel azimuth and course joint re-estimation method for compact HFSWR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(2): 1041–1051. doi: 10.1109/TGRS.2019.2943065
[4]	SUN Weifeng, DAI Yongshou, JI Yonggang, et al. Vessel target tracking exploiting frequency diversity for dual-frequency HFSWR[C]. 2016 CIE International Conference on Radar (RADAR), Guangzhou, China, 2016: 1–4.
[5]	NIKOLIC D, STOJKOVIC N, and LEKIC N. Maritime over the horizon sensor integration: High frequency surface-wave-radar and automatic identification system data integration algorithm[J]. Sensors, 2018, 18(4): 1147. doi: 10.3390/s18041147
[6]	STOJKOVIC N, NIKOLIC D, and PUZOVI? S. Density based clustering data association procedure for real–time HFSWRs tracking at OTH distances[J]. IEEE Access, 2020, 8: 39907–39919. doi: 10.1109/ACCESS.2020.2976481
[7]	WANG Jun, ZENG Yajun, WEI Shaoming, et al. Multi-sensor track-to-track association and spatial registration algorithm under incomplete measurements[J]. IEEE Transactions on Signal Processing, 2021, 69: 3337–3350. doi: 10.1109/TSP.2021.3084533
[8]	NAZARI M, PASHAZADEH S, and MOHAMMAD-KHANLI L. An adaptive density-based fuzzy clustering track association for distributed tracking system[J]. IEEE Access, 2019, 7: 135972–135981. doi: 10.1109/ACCESS.2019.2941184
[9]	靳冰洋, 劉崢, 秦基凱. 基于灰色關聯(lián)度的兩級實時航跡關聯(lián)算法[J]. 兵工學報, 2020, 41(7): 1330–1338. doi: 10.3969/j.issn.1000-1093.2020.07.010 JIN Bingyang, LIU Zheng, and QIN Jikai. Two-stage real-time track correlation algorithm based on gray correlation[J]. Acta Armamentarii, 2020, 41(7): 1330–1338. doi: 10.3969/j.issn.1000-1093.2020.07.010
[10]	蔡昌愷, 朱浩, 余仁偉, 等. 基于航跡全局和局部混合特征的航跡關聯(lián)算法[J]. 儀器儀表學報, 2020, 41(10): 32–42. doi: 10.19650/j.cnki.cjsi.J2006793 CAI Changkai, ZHU Hao, YU Renwei, et al. Track-to-track association by the global and local mixture feature[J]. Chinese Journal of Scientific Instrument, 2020, 41(10): 32–42. doi: 10.19650/j.cnki.cjsi.J2006793
[11]	RAGHU J, SRIHARI P, THARMARASA R, et al. Comprehensive track segment association for improved track continuity[J]. IEEE Transactions on Aerospace and Electronic Systems, 2018, 54(5): 2463–2480. doi: 10.1109/TAES.2018.2820364
[12]	周學平, 李佳杰, 趙曉蓮, 等. 基于匈牙利法的機載雷達中斷航跡關聯(lián)[J]. 現(xiàn)代雷達, 2021, 43(6): 42–48. doi: 10.16592/j.cnki.1004-7859.2021.06.008 ZHOU Xueping, LI Jiajie, ZHAO Xiaolian, et al. Airborne radar track segment association based on hungarian algorithm[J]. Modern Radar, 2021, 43(6): 42–48. doi: 10.16592/j.cnki.1004-7859.2021.06.008
[13]	CHANG W, JAU Y T, SU S L, et al. Gale-Shapley-algorithm based resource allocation scheme for device-to-device communications underlaying downlink cellular networks[C]. 2016 IEEE Wireless Communications and Networking Conference, Doha, Qatar, 2016: 1–6.
[14]	PITTEL B. One-sided version of Gale-Shapley proposal algorithm and its likely behavior under random preferences[J]. Discrete Applied Mathematics, 2021, 292: 1–18. doi: 10.1016/j.dam.2020.12.020