CLC number: TN953
On-line Access: 2021-07-12
Received: 2020-02-06
Revision Accepted: 2020-07-30
Crosschecked: 2021-06-01
Cited: 0
Clicked: 3957
Liping Wang, Ronghui Zhan, Yuan Huang, Jun Zhang, Zhaowen Zhuang. Joint tracking and classification of extended targets with complex shapes[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.2000061 @article{title="Joint tracking and classification of extended targets with complex shapes", %0 Journal Article TY - JOUR
复杂形状的扩展目标联合跟踪与分类国防科技大学自动目标识别重点实验室,中国长沙市,410073 摘要:本文解决具有复杂形状的单扩展目标联合跟踪与分类(joint tracking and classification, JTC)问题。为描述复杂形状,首先利用随机超曲面模型(random hypersurface model, RHM)将空间扩展状态建模为星凸形状,并将其作为目标分类的特征信息。利用两个向量对目标状态建模,以减轻高维状态空间和严重非线性观测模型对目标状态估计的影响,并利用归一化傅立叶描述子的欧氏距离度量获得类别概率更新的解析解。因此,该方法被称为"JTC-RHM方法"。此外,为解决检测不确定和杂波情况下的单扩展目标JTC问题,将所提JTC-RHM方法整合到Bernoulli滤波框架中,提出JTC-RHM-Ber滤波算法。特别地,推导了该滤波算法的递推表达式。仿真结果表明:(1)与基于随机矩阵模型的JTC算法相比,所提JTC-RHM方法能更准确地对不同形状、相似大小的目标进行分类;(2)与基于星凸RHM的扩展目标跟踪算法相比,所提算法对目标状态性能估计更优;(3)所提JTC-RHM-Ber滤波算法在状态检测和估计方面具有良好性能,能够正确地实现目标分类。 关键词组: Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
Reference[1]Angelova D, Mihaylova L, 2006. Joint target tracking and classification with particle filtering and mixture Kalman filtering using kinematic radar information. Dig Signal Process, 16(2):180-204. [2]Angelova D, Mihaylova L, Petrov N, et al., 2013. A convolution particle filtering approach for tracking elliptical extended objects. Proc 16th Int Conf on Information Fusion, p.1542-1549. [3]Baum M, Hanebeck UD, 2014. Extended object tracking with random hypersurface models. IEEE Trans Aerosp Electron Syst, 50(1):149-159. [4]Baum M, Klumpp V, Hanebeck UD, 2010. A novel Bayesian method for fitting a circle to noisy points. Proc 13th Int Conf on Information Fusion, p.1-6. [5]Baum M, Faion F, Hanebeck UD, 2012. Modeling the target extent with multiplicative noise. Proc 15th Int Conf on Information Fusion, p.2406-2412. [6]Beard M, Reuter S, Granström K, et al., 2016. Multiple extended target tracking with labeled random finite sets. IEEE Trans Signal Process, 64(7):1638-1653. [7]Cao W, Lan J, Li XR, 2016. Conditional joint decision and estimation with application to joint tracking and classification. IEEE Trans Syst Man Cybern Syst, 46(4):459-471. [8]Cao W, Lan J, Li XR, 2018. Extended object tracking and classification using radar and ESM sensor data. IEEE Signal Process Lett, 25(1):90-94. [9]de Freitas A, Mihaylova L, Gning A, et al., 2019. A box particle filter method for tracking multiple extended objects. IEEE Trans Aerosp Electron Syst, 55(4):1640-1655. [10]Eryildirim A, Guldogan MB, 2016. A Bernoulli filter for extended target tracking using random matrices in a UWB sensor network. IEEE Sens J, 16(11):4362-4373. [11]Feldmann M, Fränken D, Koch W, 2011. Tracking of extended objects and group targets using random matrices. IEEE Trans Signal Process, 59(4):1409-1420. [12]Gilholm K, Salmond D, 2005. Spatial distribution model for tracking extended objects. IEE Proc Radar Sonar Navig, 152(5):364-371. [13]Granström K, Lundquist C, Orguner O, 2012. Extended target tracking using a Gaussian-mixture PHD filter. IEEE Trans Aerosp Electron Syst, 48(4):3268-3286. [14]Granström K, Reuter S, Meissner D, et al., 2014. A multiple model PHD approach to tracking of cars under an assumed rectangular shape. Proc 17th Int Conf on Information Fusion, p.1-8. [15]Granström K, Willett P, Bar-Shalom Y, 2015. An extended target tracking model with multiple random matrices and unified kinematics. Proc 18th Int Conf on Information Fusion, p.1007-1014. [16]Granström K, Baum M, Reuter S, 2017. Extended object tracking: introduction, overview, and applications. J Adv Inform Fus, 12(2):139-174. [17]Hirscher T, Scheel A, Reuter S, et al., 2016. Multiple extended object tracking using Gaussian processes. Proc 19th Int Conf on Information Fusion, p.1-8. [18]Hu Q, Ji HB, Zhang YQ, 2018. A standard PHD filter for joint tracking and classification of maneuvering extended targets using random matrix. Signal Process, 144:352-363. [19]Jiang H, Zhan K, Xu L, 2015. Joint tracking and classification with constraints and reassignment by radar and ESM. Dig Signal Process, 40:213-223. [20]Knill C, Scheel A, Dietmayer K, 2016. A direct scattering model for tracking vehicles with high-resolution radars. Proc IEEE Intelligent Vehicles Symp, p.298-303. [21]Koch JW, 2008. Bayesian approach to extended object and cluster tracking using random matrices. IEEE Trans Aerosp Electron Syst, 44(3):1042-1059. [22]Lan J, Li XR, 2013. Joint tracking and classification of extended object using random matrix. Proc 16th Int Conf on Information Fusion, p.1550-1557. [23]Lan J, Li XR, 2014. Tracking of maneuvering non-ellipsoidal extended object or target group using random matrix. IEEE Trans Signal Process, 62(9):2450-2463. [24]Lan J, Li XR, 2016. Tracking of extended object or target group using random matrix: new model and approach. IEEE Trans Aerosp Electron Syst, 52(6):2973-2989. [25]Magnant C, Kemkemian S, Zimmer L, 2018. Joint tracking fand classification for extended targets in maritime surveillance. Proc IEEE Radar Conf, p.1117-1122. [26]Mahler RPS, 2007. Statistical Multisource-Multitarget Information Fusion. Artech House, Boston, USA. [27]Mahler RPS, 2014. Advances in Statistical Multisource-Multitarget Information Fusion. Artech House, Boston, USA. [28]Mihaylova L, Carmi AY, Septier F, et al., 2014. Overview of Bayesian sequential Monte Carlo methods for group and extended object tracking. Dig Signal Process, 25:1-16. [29]Ristic B, Gordon N, Bessell A, 2004. On target classification using kinematic data. Inform Fus, 5(1):15-21. [30]Ristic B, Vo BT, Vo BN, et al., 2013. A tutorial on Bernoulli filters: theory, implementation and applications. IEEE Trans Signal Process, 61(13):3406-3430. [31]Schuhmacher D, Vo BT, Vo BN, 2008. A consistent metric for performance evaluation of multi-object filters. IEEE Trans Signal Process, 56(8):3447-3457. [32]Sun LF, Lan J, Li XR, 2018. Joint tracking and classification of extended object based on support functions. IET Radar Sonar Navig, 12(7):685-693. [33]Wahlström N, Özkan E, 2015. Extended target tracking using Gaussian processes. IEEE Trans Signal Process, 63(16):4165-4178. [34]Yang SS, Baum M, 2016. Second-order extended Kalman filter for extended object and group tracking. Proc 19th Int Conf on Information Fusion, p.1-7. [35]Yang SS, Baum M, 2017. Extended Kalman filter for extended object tracking. Proc IEEE Int Conf on Acoustics, Speech and Signal Processing, p.4386-4390. [36]Zhao YJ, Belkasim S, 2012. Multiresolution Fourier descriptors for multiresolution shape analysis. IEEE Signal Process Lett, 19(10):692-695. Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou
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