Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Shuncheng Tan"'
Publikováno v:
IEEE Access, Vol 9, Pp 94438-94453 (2021)
A robust generalized labeled multi-Bernoulli (GLMB) filter is presented to perform multitarget tracking (MTT) with unknown non-stationary heavy-tailed measurement noise (HTMN). The HTMN is modeled as a multivariate Student’s t-distribution with unk
Externí odkaz:
https://doaj.org/article/09742fc148a84e5788c3ad47a4966c98
Publikováno v:
The Journal of Engineering (2019)
To address the problem of target detection and tracking with the range ambiguous radar in low signal-to-noise ratio environment, a novel weak target detection and tracking algorithm based on the compressed sensing (CS) and multiple model particle fil
Externí odkaz:
https://doaj.org/article/8e6adac5329549798f2196ac2bbd7c0b
Publikováno v:
Information Sciences. 616:303-329
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f393d88522f247df15292325d54d9cef
https://doi.org/10.1016/j.ins.2022.10.061
https://doi.org/10.1016/j.ins.2022.10.061
Publikováno v:
2022 5th International Conference on Information Communication and Signal Processing (ICICSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e24c4959c5ffce9e0abc7e0afeff982
https://doi.org/10.1109/icicsp55539.2022.10050606
https://doi.org/10.1109/icicsp55539.2022.10050606
Publikováno v:
IEEE Access, Vol 9, Pp 94438-94453 (2021)
A robust generalized labeled multi-Bernoulli (GLMB) filter is presented to perform multitarget tracking (MTT) with unknown non-stationary heavy-tailed measurement noise (HTMN). The HTMN is modeled as a multivariate Student’s t-distribution with unk
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94654364c545a03cda4285296680e88d
https://doi.org/10.1109/access.2021.3092021
https://doi.org/10.1109/access.2021.3092021
Publikováno v:
2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC).
Based on the Cubature Kalman filter algorithm (CKF) algorithm, we present a new particle filtering algorithm. To construct the importance density of samples, the importance density function is generated by a new framework, in which the state of each
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0bd1b07bd06b89d08f1904a870465253
https://doi.org/10.1109/iaeac50856.2021.9391057
https://doi.org/10.1109/iaeac50856.2021.9391057
Publikováno v:
FUSION
To solve the problem of multi-target tracking with heavy-tailed process noise and measurement noise, a Student's t mixture $\delta$ -generalized labeled multi-Bernoulli ( $\delta$ -GLMB) filter is proposed for nonlinear systems. A third-degree Spheri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eeaeb003aa3595bebce11481ff11f22e
https://doi.org/10.23919/fusion45008.2020.9190250
https://doi.org/10.23919/fusion45008.2020.9190250
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789811394089
CSPS
CSPS
To address the problem of detection and tracking for the near-space weak targets under range ambiguity, an improved approach is proposed using Dynamic Programming (DP) within the track-before-detect (TBD) framework. Firstly, the target information is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac55bdaaa3fbc3641c067152f38599e7
https://doi.org/10.1007/978-981-13-9409-6_120
https://doi.org/10.1007/978-981-13-9409-6_120
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789811394089
CSPS
CSPS
The existing literatures usually adopt the linear method to obtain the location error which is usually evaluated by geometrical dilution of precision (GDOP) in nonlinear passive location systems. However, the linear method is not always suitable in a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa6e605a3606939c22567d6bf54911b2
https://doi.org/10.1007/978-981-13-9409-6_73
https://doi.org/10.1007/978-981-13-9409-6_73
Publikováno v:
2019 22th International Conference on Information Fusion (FUSION).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17f881e3fd14c053c1de7e37c96f68f2
https://doi.org/10.23919/fusion43075.2019.9011245
https://doi.org/10.23919/fusion43075.2019.9011245