2005
DOI: 10.1109/tits.2005.858784
|View full text |Cite
|
Sign up to set email alerts
|

Data Association and Tracking for Automotive Radar Networks

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

1
43
0

Year Published

2012
2012
2020
2020

Publication Types

Select...
4
2
1

Relationship

0
7

Authors

Journals

citations
Cited by 66 publications
(44 citation statements)
references
References 8 publications
1
43
0
Order By: Relevance
“…The combination of measured ranges that do not belong together will lead to ghost-target situations at the output of the quadratic position-fixing stage. Classical way to solve position-estimation problem consisting in data-association and quadratic position-fixing algorithm (usually called the top-down approach) can carry a technical challenge in dense multi-target situations [11]. Because of this, an alternative position-estimation process is chosen for the proposed system.…”
Section: B Data Fusionmentioning
confidence: 99%
See 1 more Smart Citation
“…The combination of measured ranges that do not belong together will lead to ghost-target situations at the output of the quadratic position-fixing stage. Classical way to solve position-estimation problem consisting in data-association and quadratic position-fixing algorithm (usually called the top-down approach) can carry a technical challenge in dense multi-target situations [11]. Because of this, an alternative position-estimation process is chosen for the proposed system.…”
Section: B Data Fusionmentioning
confidence: 99%
“…For an assumed position t taken as a reference, optimal data association can be performed based on a simple minimum-distance calculation. This approach is referred as bottom-up processing [11]. To obtain reference points for assumed target positions, a grid is used over the entire observation area as shown in Fig.…”
Section: B Data Fusionmentioning
confidence: 99%
“…in [12,18,[20][21][22][23][24]. Its solution for single person scenarios can be considered successfully solved.…”
Section: Introductionmentioning
confidence: 99%
“…The presence of multiple targets results in additional problems, such as ghost appearance, changing of target tracks or mutual shielding among people. Ghosts are defined as false targets originating for example in the localization phase when the measured bistatic ranges applied for the target position estimation do not belong to the same target [22]. To avoid ghosts, proper association of data received from all receiving channels needs to be done (e.g.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation