Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Zong-Xiang Liu"'
Publikováno v:
IEEE Access, Vol 9, Pp 2100-2109 (2021)
The δ-generalized labeled multi-Bernoulli (δ-GLMB) filter is an efficient approach for multiobject tracking in case of high clutter density and low detection probability. However, the formulation of the original δ-GLMB filter requires that the bir
Externí odkaz:
https://doaj.org/article/ace8cd32e496484e81d9c3c655682b7c
Publikováno v:
IEEE Access, Vol 8, Pp 118235-118244 (2020)
This work proposes a marginal distribution multi-target Bayes filter with assignment of measurements to track multiple targets in the presence of an unknown and variable number of targets, clutter, and missed detections. Mathematically, the associati
Externí odkaz:
https://doaj.org/article/a17dea44c4a249a89e5d73d9cb890d8f
Autor:
Zong-Xiang Liu, Bing-Jian Huang
Publikováno v:
IEEE Access, Vol 7, Pp 92322-92328 (2019)
This paper proposes a novel labeled multi-Bernoulli (LMB) filter for jump Markov systems (JMS) to track the multiple maneuvering objects under glint noise. By modeling the glint noise as a Student's t-distribution and using the variational Bayesian m
Externí odkaz:
https://doaj.org/article/ccdba22b8729489c83960d12756ae767
Publikováno v:
Sensors, Vol 17, Iss 5, p 972 (2017)
Novel auxiliary truncated unscented Kalman filtering (ATUKF) is proposed for bearings-only maneuvering target tracking in this paper. In the proposed algorithm, to deal with arbitrary changes in motion models, a modified prior probability density fun
Externí odkaz:
https://doaj.org/article/d40b1d8061c045ec82a2e82e8da92334
Publikováno v:
Sensors, Vol 17, Iss 2, p 373 (2017)
Tracking the target that maneuvers at a variable turn rate is a challenging problem. The traditional solution for this problem is the use of the switching multiple models technique, which includes several dynamic models with different turn rates for
Externí odkaz:
https://doaj.org/article/35c83f2417364afe8e3f911a8947f4d5
Publikováno v:
In AEUE - International Journal of Electronics and Communications January 2015 69(1):281-289
Publikováno v:
IEEE Access. 9:2100-2109
The $\delta $ -generalized labeled multi-Bernoulli ( $\delta $ -GLMB) filter is an efficient approach for multi-object tracking in case of high clutter density and low detection probability. However, the formulation of the original $\delta $ -GLMB fi
Adaptive measurement-assignment marginal multi-target Bayes filter with logic-based track initiation
Publikováno v:
Digital Signal Processing. 129:103636
Publikováno v:
Digital Signal Processing. 117:103156
This paper proposes a marginal multi-object Bayesian filter with multiple hypotheses to track multiple objects in the presence of object appearing and object disappearing, missed detection and clutter. This filter delivers the probability of existenc
Autor:
Xiu Jiang Tang, Zong Xiang Liu
Publikováno v:
2018 14th IEEE International Conference on Signal Processing (ICSP).
The marginal distribution Bayes (MDB) filter is an efficient method for tracking a time-varying and unknown number of targets in the existence of clutter, noise, and detection uncertainty. The MDB filter propagates the marginal distributions and exis