Adaptive Measurement Partitioning Algorithm for a Gaussian Inverse Wishart PHD Filter that Tracks Closely Spaced Extended Targets
Use of the Gaussian inverse Wishart probability hypothesis density (GIW-PHD) filter has demonstrated promise as an approach to track an unknown number of extended targets. However, when targets of various sizes are spaced closely together and performing maneuvers, estimation errors will occur becaus...
Main Authors: | P. Li, H. Ge, J. Yang |
---|---|
Format: | Article |
Language: | English |
Published: |
Spolecnost pro radioelektronicke inzenyrstvi
2017-06-01
|
Series: | Radioengineering |
Subjects: | |
Online Access: | https://www.radioeng.cz/fulltexts/2017/17_02_0573_0580.pdf |
Similar Items
-
Two Measurement Set Partitioning Algorithms for the Extended Target Probability Hypothesis Density Filter
by: Yulan Han, et al.
Published: (2019-06-01) -
IPDA filters in the sense of Gaussian mixture PHD algorithm
by: Radosavljević Zvonko
Published: (2016-01-01) -
Strong Tracking PHD Filter Based on Variational Bayesian with Inaccurate Process and Measurement Noise Covariance
by: Zhentao Hu, et al.
Published: (2021-02-01) -
Online Adapting the Magnitude of Target Birth Intensity in the PHD Filter
by: Tiancheng LI, et al.
Published: (2014-03-01) -
A Measurement Set Partitioning Algorithm Based on CFSFDP for Multiple Extended Target Tracking in PHD Filter
by: Y. Gong, et al.
Published: (2021-06-01)