Multi-Target Track Initiation in Heavy Clutter Article Swipe
Xu Li
,
Ruzhen Lou
,
Chuanbin Zhang
,
Bo Lang
,
Weiyue Ding
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.32604/cmc.2022.027400
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.32604/cmc.2022.027400
In the heavy clutter environment, the information capacity is large, the relationships among information are complicated, and track initiation often has a high false alarm rate or missing alarm rate. Obviously, it is a difficult task to get a high-quality track initiation in the limited measurement cycles. This paper studies the multi-target track initiation in heavy clutter. At first, a relaxed logic-based clutter filter algorithm is presented. In the algorithm, the raw measurement is filtered by using the relaxed logic method. We not only design a kind of incremental and adaptive filtering gate, but also add the angle extrapolation based on polynomial extrapolation. The algorithm eliminates most of the clutter and obtains the environment with high detection rate and less clutter. Then, we propose a fuzzy sequential Hough transform-based track initiation algorithm. The algorithm establishes a new meshing rule according to system noise to balance the relationship between the grid granularity and the track initiation quality. And a flexible superposition matrix based on fuzzy clustering is constructed, which avoids the transformation error caused by 0–1 voting method in traditional Hough transform. In addition, the algorithm allows the superposition matrixes of nonadjacent cycles to be associated to overcome the shortcoming that the track can’t be initiated in time when the measurements appear in an intermittent way. And a slope verification method is introduced to detect formation-intensive serial tracks. Last, the sliding window method is employed to feedback the track initiation results timely and confirm the track. Simulation results verify that the proposed algorithms can initiate the tracks accurately in heavy clutter.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.32604/cmc.2022.027400
- https://file.techscience.com/ueditor/files/cmc/TSP_CMC-72-3/TSP_CMC_27400/TSP_CMC_27400.pdf
- OA Status
- diamond
- Cited By
- 2
- References
- 33
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4226217571
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4226217571Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.32604/cmc.2022.027400Digital Object Identifier
- Title
-
Multi-Target Track Initiation in Heavy ClutterWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-01Full publication date if available
- Authors
-
Xu Li, Ruzhen Lou, Chuanbin Zhang, Bo Lang, Weiyue DingList of authors in order
- Landing page
-
https://doi.org/10.32604/cmc.2022.027400Publisher landing page
- PDF URL
-
https://file.techscience.com/ueditor/files/cmc/TSP_CMC-72-3/TSP_CMC_27400/TSP_CMC_27400.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://file.techscience.com/ueditor/files/cmc/TSP_CMC-72-3/TSP_CMC_27400/TSP_CMC_27400.pdfDirect OA link when available
- Concepts
-
Clutter, Computer science, Algorithm, Constant false alarm rate, Filter (signal processing), Hough transform, Artificial intelligence, Track (disk drive), Fuzzy logic, Computer vision, Radar, Image (mathematics), Operating system, TelecommunicationsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2Per-year citation counts (last 5 years)
- References (count)
-
33Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W3198427877, https://openalex.org/W2962568725, https://openalex.org/W2624196052, https://openalex.org/W3019175418, https://openalex.org/W6740129281, https://openalex.org/W6782850793, https://openalex.org/W4200230997, https://openalex.org/W6774461220, https://openalex.org/W6786182812, https://openalex.org/W6774950397, https://openalex.org/W3080276834, https://openalex.org/W2904852523, https://openalex.org/W2956157098, https://openalex.org/W6766564201, https://openalex.org/W3045517781, https://openalex.org/W6754781752, https://openalex.org/W6760247559, https://openalex.org/W6756340786, https://openalex.org/W2905284510, https://openalex.org/W6789544488, https://openalex.org/W2551760731, https://openalex.org/W3214128139, https://openalex.org/W6772674070, https://openalex.org/W3090156053, https://openalex.org/W2979762019, https://openalex.org/W3049294252, https://openalex.org/W6776619813, https://openalex.org/W2733768486, https://openalex.org/W6756970291, https://openalex.org/W3087934602, https://openalex.org/W3109700187, https://openalex.org/W2998539612, https://openalex.org/W2965816217 |
| referenced_works_count | 33 |
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| corresponding_author_ids | https://openalex.org/A5100342477 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I151727225, https://openalex.org/I194450716 |
| citation_normalized_percentile.value | 0.60718292 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |