Labelled GM-CBMEMBER filter with adaptive track initiation
Hemin Sun, Muyang Luo, Xiaobiao Wu and 2 more
The Journal of Engineering · 2019
doi:10.1049/joe.2019.0446 (opens in a new tab)
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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.
Abstract licence: CC BY-ND
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