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Article

Adaptive Target Birth Intensity Multi-Bernoulli Filter with Noise-Based Threshold

School of Electronic Engineering, Xidian University, Xi’an 710071, China
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Sensors 2019, 19(5), 1120; https://doi.org/10.3390/s19051120
Received: 23 January 2019 / Revised: 27 February 2019 / Accepted: 27 February 2019 / Published: 5 March 2019
(This article belongs to the Section Physical Sensors)
Adaptively modeling the target birth intensity while maintaining the filtering efficiency is a challenging issue in multi-target tracking (MTT). Generally, the target birth probability is predefined as a constant and only the target birth density is considered in existing adaptive birth models, resulting in deteriorated target tracking accuracy, especially in the target appearing cases. In addition, the existing adaptive birth models also give rise to a decline in operation efficiency on account of the extra birth modeling calculations. To properly adapt the real variation of the number of newborn targets and improve the multi-target tracking performance, a novel fast sequential Monte Carlo (SMC) adaptive target birth intensity cardinality balanced multi-target multi-Bernoulli (CBMeMBer) filter is proposed in this paper. Through adaptively conducting the target birth probability in a pre-processing step, which incorporates the information of current measurements to correct the pre-setting of the target birth probability, the proposed filter can truly adapt target birth cases and achieve better tracking accuracy. Moreover, the implementation efficiency can be improved significantly by employing a measurement noise-based threshold in the likelihood calculations of the multi-target updating. Simulation results verify the effectiveness of the proposed filter. View Full-Text
Keywords: measurement likelihood; multi-Bernoulli; multi-target tracking; random finite sets; target birth model; threshold measurement likelihood; multi-Bernoulli; multi-target tracking; random finite sets; target birth model; threshold
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MDPI and ACS Style

Hu, X.; Ji, H.; Liu, L. Adaptive Target Birth Intensity Multi-Bernoulli Filter with Noise-Based Threshold. Sensors 2019, 19, 1120. https://doi.org/10.3390/s19051120

AMA Style

Hu X, Ji H, Liu L. Adaptive Target Birth Intensity Multi-Bernoulli Filter with Noise-Based Threshold. Sensors. 2019; 19(5):1120. https://doi.org/10.3390/s19051120

Chicago/Turabian Style

Hu, Xiaolong, Hongbing Ji, and Long Liu. 2019. "Adaptive Target Birth Intensity Multi-Bernoulli Filter with Noise-Based Threshold" Sensors 19, no. 5: 1120. https://doi.org/10.3390/s19051120

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