Title :
Research on measurement set partitioning method for tracking multiple extended targets
Author :
Hongyan Zhu ; Pandeng Zhang ; Tingting Ma
Author_Institution :
Sch. of Electron. & Inf. Eng., Xi´an Jiaotong Univ., Xi´an, China
Abstract :
In extended target tracking, it is a critical step to implement the measurement set partitioning, which aims to partition the whole measurement set into several distinct clusters. When multiple extended targets are in close proximity, there are great challenges. To deal with this problem, we introduce the DBSCAN-FCM partition to the Gaussian inverse Wishart PHD (GIW-PHD) filter, which combines the density based spatial clustering of application with noise (DBSCAN) and the Fuzzy C means (FCM) clustering. Selected simulation results are provided to demonstrate the performance superiority of the proposed method compared with other competing algorithms.
Keywords :
Gaussian processes; filtering theory; fuzzy set theory; pattern clustering; target tracking; DBSCAN-FCM partition; FCM clustering; GIW-PHD filter; Gaussian inverse Wishart PHD filter; density based spatial clustering of application with noise; fuzzy C means clustering; measurement set partitioning method; multiple extended target tracking; Clustering algorithms; Density measurement; Filtering theory; Partitioning algorithms; Shape; Target tracking; Time measurement; Clustering; Extended Target; Measurement Set Partitioning;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7162642
