Back to Search Start Over

Labelled GM-CBMEMBER filter with adaptive track initiation

Authors :
Hemin Sun
Muyang Luo
Xiaobiao Wu
Xin Xie
Zhimin Jiang
Source :
The Journal of Engineering (2019)
Publication Year :
2019
Publisher :
Wiley, 2019.

Abstract

The initial Gaussian mixture cardinality balanced multi-target multi-Bernoulli (GM-CBMeMBer) filter does not provide track information and assumes that the target birth intensity is known as a priori, but in reality the target may appear anywhere in the detection area. Therefore, the study proposes a labelled GM-CBMeMBer filter with adaptive track initiation. First, the filter introduces track label information and selects the measurements of newborn targets in the prediction process. In addition, it also makes full use of the Doppler information of the airborne Doppler radar. Then, the position estimate and velocity estimate of newborn targets are calculated by using position measurements converted and Doppler measurements, respectively. Further the label information in the prediction process is inherited during the update process, and the target states are updated sequentially with the Doppler measurements after having been updated by using position measurements. Monte–Carlo experiments show that the proposed filter can perform adaptive track initiation effectively, with good tracking performance, and provide target track information well.

Details

Language :
English
ISSN :
20513305
Database :
Directory of Open Access Journals
Journal :
The Journal of Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.4b430d3658641b285309b8f1fa642c7
Document Type :
article
Full Text :
https://doi.org/10.1049/joe.2019.0446