Star-convex extended target student’s t filter for heavy tailed noise

Abstract

Abstract: Aiming at the problem of irregular shape extended target tracking with nonlinear non-Gaussian heavy tailed noise, this paper proposes a star-convex extended target nonlinear student’s t filter algorithm based on a random hypersurface model. First, in a system with non-Gaussian heavy tailed process and measurement noise, a robust student’s t based nonlinear filter is given based on the student’s t distribution. Then, random hypersurface model (RHM) is used to describe the measurement source distribution of any star-convex extended target, and star-convex extended target student’s t filter is proposed. Finally, numerical simulation example shows the validity and feasibility of the proposed method.

Key words: extended target tracking, random hypersurface model, robust student’s t based nonlinear filter, student’s t distribution

CLC Number:

TP273

CHEN Hui, ZHANG Xing-xing, YANG Wen-yu. Star-convex extended target student’s t filter for heavy tailed noise[J]. Journal of Lanzhou University of Technology, 2021, 47(5): 85-92.

References

[1] GRANSTRÖM K,BAUM M.Extended object tracking:introduction,overview and applications [J].Journal of Advances in Information Fusion,2017,12(2):139-174.
[2] XIA Y,GRANSTROM K,SVENSSON L,et al.Extended target Poisson multi-Bernoulli filter [C/OL].[2020-06-10].https://arxiv.org/pdf/1801.01353.pdf.
[3] XIA Y,GRANSTROM K,SVENSSON L,et al.Extended target Poisson multi-Bernoulli mixture trackers based on sets of trajectories [C]//The 22th International Conference on Information Fusion.Ottawa,Canada:IEEE,2019:1-8.
[4] GRANSTRÖM K,ORGUNER U,MAHLER R,et al.Corrections on:extended target tracking using a Gaussian-mixture PHD filter [J].IEEE Transactions on Aerospace and Electronic Systems,2017,53(2):1055-1058.
[5] 陈辉,杜金瑞,韩崇昭.自适应不规则形状扩展目标跟踪算法 [J].控制理论与应用,2018,35(8):1111-1119.
[6] RISTIC B,SALMOND D.A study of a nonlinear filtering problem for tracking an extended target [C]//The 7th International Conference on Information Fusion.Stockholm,Sweden:IEEE,2004:503-509.
[7] FELDMANN M,FRANKEN D,KOCH W.Tracking of extended objects and group targets using random matrices [J].IEEE Transactions on Signal Processing,2011,59(4):1409-1420.
[8] 陈辉,赵维娓.一种多扩展目标非线性高斯逆Wishart概率假设密度滤波器 [J].兰州理工大学学报,2019,45(3):95-100.
[9] LAN J,LI X R.Tracking of extended object or target group using random matrix―Part Ⅱ:Irregular object [C]//The 15th International Conference on Information Fusion.Singapore:IEEE,2012:2185-2192.
[10] 陈辉,杜金瑞,韩崇昭.基于星凸形随机超曲面模型多扩展目标多伯努利滤波器 [J].自动化学报,2020,46(5):909-922.
[11] BAUM M,HANEBECK D.Extended object tracking with random hypersurface models [J].IEEE Transactions on Aerospace and Electronic Systems,2014,50(1):149-159.
[12] BAUM M,NOACK B,HANEBECK D.Extended object and group tracking with elliptic random hypersurface models [C]//The 13th International Conference on Information Funsion.Sanya,China:IEEE,2010:2230-2235.
[13] HUANG Y,ZHANG Y.Robust student’s t-based stochastic cubature filter for nonlinear systems with heavy-tailed process and measurement noises [J].IEEE Access,2017:7964-7974.
[14] TRONARP F,KARVONEN T,SARKKA S,et al.Student’s t -filters for noise scale estimation [J].IEEE Signal Processing Letters,2019,26(2):352-356.
[15] HUANG Y,ZHANG Y,LI N,et al.A Novel robust student’s t -based Kalman filter [J].IEEE Transactions on Aerospace and Electronic Systems,2017,53(3):1545-1554.
[16] HUANG Y,ZHANG Y,LI N,et al.Robust student’s t based nonlinear filter and smoother [J].IEEE Transactions on Aerospace and Electronic Systems,2016,52(5):2586-2596.
[17] 程然,缪礼锋,王婷婷.带厚尾噪声的鲁棒Student’s t容积滤波器 [J].控制理论与应用,2019,36(7):1174-1181.
[18] ROTH M,ÖZKAN E,GUSTAFSSON F.A student’s t filter for heavy tailed process and measurement noise [C]//International Conference on Acoustics,Speech and Signal Processing.[S.l.]:IEEE,2013:5770-5774.
[19] LAN J,LI X R.Extended-object or group-target tracking using random matrix with nonlinear measurements [J].IEEE Transactions on Signal Processing,2019,67(19):5130-5142.
[20] LIAN F,HAN C Z,LIU W F,et al.Sequential Monte Carlo implementation and state extraction of the group probability hypothesis density filter for partly unresolvable group targets-tracking problem [J].Iet Radar Sonar & Navigation,2010,4(5):685-702.