A belief propagation algorithm based on track‐before‐detect for tracking low‐observable and manoeuvering targets using multiple sensors Article Swipe
Chenghu Cao
,
Haisheng Huang
,
Xin Li
,
Yongbo Zhao
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1049/rsn2.12673
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1049/rsn2.12673
It is notoriously challenging work to track an unknown number of low‐observable manoeuvering targets. In this paper, a sequential Bayesian inference method based on the multiple‐model dynamic model and track‐before‐detect measurement (TBD) model is proposed for tracking low‐observable manoeuvering targets using multiple sensors. The multiple‐model dynamic model is capable to characterise the dynamic behaviour of manoeuvering targets. The TBD measurement model can completely capture an echo signal without any preprocessing, furtherly handling with low‐observable targets. The authors’ proposed method is based on a new multi‐sensor statistical model that allows targets to interact and contribute to more than one data cell for the pixeled image TBD approach. Based on the factor graph representing the multi‐sensor statistical model, the marginal posterior densities are derived by performing the message passing equations of the proposed belief propagation algorithm for target detection and target state estimation. The simulation results validate that the computational complexity of our proposed multi‐sensor BP‐TBD algorithm scales in the number of sensor nodes and demonstrate that its performance is superior among the state‐of‐the‐art multi‐sensor TBD methods.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1049/rsn2.12673
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/rsn2.12673
- OA Status
- gold
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404874526
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4404874526Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1049/rsn2.12673Digital Object Identifier
- Title
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A belief propagation algorithm based on track‐before‐detect for tracking low‐observable and manoeuvering targets using multiple sensorsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-11-30Full publication date if available
- Authors
-
Chenghu Cao, Haisheng Huang, Xin Li, Yongbo ZhaoList of authors in order
- Landing page
-
https://doi.org/10.1049/rsn2.12673Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/rsn2.12673Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/rsn2.12673Direct OA link when available
- Concepts
-
Observable, Track (disk drive), Computer science, Tracking (education), Algorithm, Belief propagation, Artificial intelligence, Computer vision, Psychology, Physics, Decoding methods, Quantum mechanics, Operating system, PedagogyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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35Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| publication_date | 2024-11-30 |
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| referenced_works | https://openalex.org/W3117447933, https://openalex.org/W3197122187, https://openalex.org/W2979653692, https://openalex.org/W4310748646, https://openalex.org/W2511568459, https://openalex.org/W2945747947, https://openalex.org/W2154353836, https://openalex.org/W3015395304, https://openalex.org/W1909771825, https://openalex.org/W2993465864, https://openalex.org/W2901168609, https://openalex.org/W2761761724, https://openalex.org/W2762588164, https://openalex.org/W2789551723, https://openalex.org/W4285293375, https://openalex.org/W3090449432, https://openalex.org/W2998168058, https://openalex.org/W3169502301, https://openalex.org/W4321788371, https://openalex.org/W2973169463, https://openalex.org/W3008383159, https://openalex.org/W4225691050, https://openalex.org/W4377000497, https://openalex.org/W3126344916, https://openalex.org/W2123378338, https://openalex.org/W1845278593, https://openalex.org/W1965106715, https://openalex.org/W2764024189, https://openalex.org/W1745301770, https://openalex.org/W3173521566, https://openalex.org/W4293660975, https://openalex.org/W4308866386, https://openalex.org/W4390830058, https://openalex.org/W3210977953, https://openalex.org/W4384916595 |
| referenced_works_count | 35 |
| abstract_inverted_index.a | 18, 83 |
| abstract_inverted_index.In | 15 |
| abstract_inverted_index.It | 1 |
| abstract_inverted_index.an | 8, 65 |
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| abstract_inverted_index.in | 157 |
| abstract_inverted_index.is | 2, 34, 48, 80, 168 |
| abstract_inverted_index.of | 11, 55, 129, 150, 160 |
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| abstract_inverted_index.to | 6, 50, 91, 95 |
| abstract_inverted_index.TBD | 59, 105, 174 |
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| abstract_inverted_index.and | 29, 93, 138, 163 |
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| abstract_inverted_index.this | 16 |
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| abstract_inverted_index.work | 5 |
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| abstract_inverted_index.model, | 116 |
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| abstract_inverted_index.paper, | 17 |
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| abstract_inverted_index.target | 136, 139 |
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| abstract_inverted_index.methods. | 175 |
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| abstract_inverted_index.sensors. | 43 |
| abstract_inverted_index.superior | 169 |
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| abstract_inverted_index.multiple‐model | 26, 45 |
| abstract_inverted_index.state‐of‐the‐art | 172 |
| abstract_inverted_index.track‐before‐detect | 30 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5024647618 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I4210102412 |
| citation_normalized_percentile.value | 0.24277224 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |