Robust Sensor Registration Based on Ridge Least Trimmed Squares
TIAN Wei1, PENG Hua-fu1,2, HUANG Gao-ming1, LIN Xiao-hong1, WANG Xue-bao1
1. College of Electronic Engineering, Naval University of Engineering, Wuhan, Hubei 430033, China;
2. Unit 92773 of the PLA, Wenzhou, Zhejiang 325807, China
Abstract：Sensor registration is the key precondition of the performance advantages of the multisensor data fusion system.In the presence of random errors,sensor biases,false alarms and missed detections,sensor registration usually works in a nonideal association envrionment.Traditional registration approches relying on the ideal association condition degrade seriously.On the other hand,traditional registration methods are sensitive to the target distribution.When targets are densely distributed,the registration problem is ill-conditioned and the estimation encounters the numerical instability phenomena.Focusing on sensor registration in the context of nonideal association and ill-condition,this paper presents the robust registration approach based on ridge least trimmed squares (RLTS).The proposed approach combines the advantages of the ridge regression (RR) and the least trimmed squares (LTS) estimation.The RLTS can deal with nonideal association and ill-condition simultaneously.Simulation results verify the robust performance of the RLTS method.
[1] ZHANG F,KNOLL A.Systematic error modeling and bias estimation[J].Sensors,2016,16(5):729.
[2] STUBBERUD S,KRAMER K,GEREMIA J.Online sensor modeling using a neural Kalman filter[J].IEEE Transactions on Instrumentation and Measurement,2007,56(4):1451-1458.
[3] BURKE J J.The SAGE real quality control fraction and its interface with BUIC Ⅱ/BUIC Ⅲ[R].MITRE Corporation,1966.
[4] ZHOU Yifeng,LEUNG H,BLANCHETTE M.Sensor alignment with earth-centered earth-fixed (ECEF) coordinate system[J].IEEE Transactions on Aerospace and Electronic systems,1999,35(2):410-418.
[5] ZHENG Ziwei,ZHU Yisheng.New least squares registration algorithm for data fusion[J].IEEE Transactions on Aerospace and Electronic Systems,2004,40(4):1410-1416.
[6] FORTUNATI S,FARINA A,GINI F,et al.Least squares estimation and Cramer-Rao type lower bounds for relative sensor registration process[J].IEEE Transactions on Signal Processing,59(3):1075-1085,2011.
[7] OKELLO N,RISTIO B.Maximum likelihood registration for multiple dissimilar sensors[J].IEEE Transactions on Aerospace and Electronic Systems,2003,39(3):1074-1083.
[8] ZHOU Yifeng,LEUNG H,YIP P C.An exact maximum likelihood registration algorithm for data fusion[J].IEEE Transactions on Signal Processing,1997,45(6):1560-1573.
[9] FORTUNATI S,GINI F,FARINA A,et al.On the application of the expectation-maximisation algorithm to the relative sensor registration problem[J].IET Radar,Sonar & Navigation,2013,7(2):191-203.
[10] 田威,王钺,山秀明,等.稳健的联合航迹关联与系统误差估计[J].清华大学学报(自然科学版),2013,53(7):946-950. TIAN Wei,WANG Yue,SHAN Xiuming,et al.Robust method for joint track association and sensor bias estimation[J].Journal of Tsinghua University (Science and Technology),2013,53(7):946-950.(in Chinese)
[11] 田威,王钺,山秀明,等.基于系统误差估计残差的错误关联检测方法[J].系统工程与电子技术,2013,35(10):2062-2068. TIAN Wei,WANG Yue,SHAN Xiuming,et al.Misassociation detection method based on the residual errors of system bias estimation[J].Systems Engineering and Electronics,2013,35(10):2062-2068.(in Chinese)
[12] 田威,黄高明.非理想关联下多传感器系统误差的稳健估计[J].电子与信息学报,2018,40(3):641-647. TIAN Wei,HUANG Gaoming.Robust multisensor bias estimation under nonideal association[J].Journal of Electronics and Information Technology,2018,40(3):641-647.(in Chinese)
[13] 田威.复杂环境下多传感器航迹关联与抗差处理[D].北京:清华大学,2014. TIAN Wei.Multisensor track-to-track association and bias removal in complex environments[D].Beijing:Tsinghua University,2014.(in Chinese)
[14] 高青,王钺,杜雄杰,等.数据融合中系统误差估计的病态性及改善方法[J].清华大学学报(自然科学版),2010,50(4):591-594. GAO Q,WANG Y,DU X J,et al.Ill-condition and registration of system error estimation in data fusion systems[J].Tsinghua Science and Technology,2010,50(4):591-594.(in Chinese)
[15] 朱洪伟,唐小明,何友.基于航迹无关模型的传感器系统误差可观测性分析[J].雷达学报,2013,2(4):454-460. ZHU H W,TANG X M,HE Y.Observability analysis of sensor bias based on the track-independent model[J].Journal of Radars,2013,2(4):454-460.(in Chinese)
[16] WU Taotao,PAN Jianghuai,QIAO Hui,et al.Ill-posedness analysis and robust estimation for multi-sensor spatial registration[A].IEEE 14th International Conference on Control,Automation,Robotics& Vision[C].Phuket,Thailand:IEEE,2016.1-6.
[17] 田威,黄高明.病态场景下多传感器系统误差的岭估计方法[J].系统工程与电子技术,2017,39(12):2704-2708. TIAN Wei,HUANG Gaoming.Multi-sensor systematic bias estimation method in ill-conditioned scenarios on the basis of ridge estimation[J].Systems Engineering and Electronics,2017,39(12):2704-2708.(in Chinese)
[18] PU Wenqiang,LIU Yafeng,YUN Junkun,et al.Optimal estimation of sensor biases for asynchronous multi-sensor registration[J/OL].arXiv Preprint,2017,ArXiv:1710.02808(2017).
[19] TAGHAVI E,THARMARASA R,KIRUBARAJAN T,et al.A practical bias estimation algorithm for multisensor-multitarget tracking[J].IEEE Transactions on Aerospace and Electronic Systems,2016,52(1):2-19.
[20] ROUSSEEUW P J,LEROY A M,WILEY J.Robust Regression and Outlier Detection[M].New York:Wiley Online Library,1987.
[21] ROUSSEEUW P J,VAN D K.Computing LTS regression for large data sets[J].Data Mining and Knowledge Discovery,Springer,2006,12:29-45.
[22] PU W,LIU Y F,YAN J,et al.Optimal estimation of sensor biases for asynchronous multi-sensor data fusion[J].Mathematical Programming,2018,170(1):357-386.
[23] OKELLO N N,CHALLA S.Joint sensor registration and track-to-track fusion for distributed trackers[J].IEEE Transactions on Aerospace and Electronic Systems,2004,40(3):808-823.
[24] HUANG D,LEUNG H,BOSSE E.A pseudomeasurement approach to simultaneous registration and track fusion[J].IEEE Transactions on Aerospace and Electronic Systems,2012,48(3):2315-2331.
[25] ZHOU Y.A Kalman filter based registration approach for multiple asynchronous sensors[R].Defence Research Establishment,Ottawa,2003.1-2.
[26] TIAN Wei,WANG Yue,SHAN Xiuming,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.
[27] 田威,王钺,山秀明,等.基于一致关联数最大化的航迹关联算法[J].航空学报,2014,35(11):3115-3122. TIAN Wei,WANG Yue,SHAN Xiuming,et al.Track-to-track association based on maximizing the consistent association number[J].Acta Aeronautica et Astronautica Sinica,2014,35(11):3115-3122.(in Chinese)
[28] TIAN Wei,WANG Yue,DU Xiongjie,et al.Reference pattern-based track-to-track association with biased data[J].IEEE Transactions on Aerospace and Electronic Systems,2016,52(1):501-512.
[29] TIAN Wei,WANG Yue,SHAN Xiuming,et al.Track-to-track association for biased data based on the reference topology feature[J].IEEE Signal Processing Letters,2014,21(4):449-453.
[30] 何友,宋强,熊伟.基于相位相关的航迹对准关联技术[J].电子学报,2010,38(12):2718-2723. HE Y,SONG Q,XIONG W.Track alignment-correlation technique based on phase correlation[J].Acta Electronica Sinica,2010,38(12):2718-2723.(in Chinese)
2019, Vol. 47 
