Distributed Joint Sensor Registration and Multitarget Tracking Via Sensor Network Article Swipe
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1902.02523
This paper addresses distributed registration of a sensor network for multitarget tracking. Each sensor gets measurements of the target position in a local coordinate frame, having no knowledge about the relative positions (referred to as drift parameters) and azimuths (referred to as orientation parameters) of its neighboring nodes. The multitarget set is modeled as an independent and identically distributed (i.i.d.) cluster random finite set (RFS), and a consensus cardinality probability hypothesis density (CPHD) filter is run over the network to recursively compute in each node the posterior RFS density. Then a suitable cost function, xpressing the discrepancy between the local posteriors in terms of averaged Kullback-Leibler divergence, is minimized with respect to the drift and orientation parameters for sensor registration purposes. In this way, a computationally feasible optimization approach for joint sensor registraton and multitarget tracking is devised. Finally, the effectiveness of the proposed approach is demonstrated through simulation experiments on both tree networks and networks with cycles, as well as with both linear and nonlinear sensors.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1902.02523
- https://arxiv.org/pdf/1902.02523
- OA Status
- green
- Cited By
- 2
- References
- 45
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2953124334
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2953124334Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.1902.02523Digital Object Identifier
- Title
-
Distributed Joint Sensor Registration and Multitarget Tracking Via Sensor NetworkWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-02-07Full publication date if available
- Authors
-
Lin Gao, Giorgio Battistelli, Luigi Chisci, Ping WeiList of authors in order
- Landing page
-
https://arxiv.org/abs/1902.02523Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1902.02523Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/1902.02523Direct OA link when available
- Concepts
-
Computer science, Cardinality (data modeling), Tracking (education), Divergence (linguistics), Wireless sensor network, Position (finance), Orientation (vector space), Node (physics), Independent and identically distributed random variables, Filter (signal processing), Tree (set theory), Algorithm, Mathematics, Random variable, Computer vision, Data mining, Statistics, Engineering, Pedagogy, Linguistics, Computer network, Philosophy, Mathematical analysis, Finance, Geometry, Structural engineering, Psychology, EconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2022: 1, 2019: 1Per-year citation counts (last 5 years)
- References (count)
-
45Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2953124334 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.1902.02523 |
| ids.doi | https://doi.org/10.48550/arxiv.1902.02523 |
| ids.mag | 2953124334 |
| ids.openalex | https://openalex.org/W2953124334 |
| fwci | |
| type | preprint |
| title | Distributed Joint Sensor Registration and Multitarget Tracking Via Sensor Network |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10711 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9994999766349792 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Target Tracking and Data Fusion in Sensor Networks |
| topics[1].id | https://openalex.org/T10249 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9247999787330627 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1705 |
| topics[1].subfield.display_name | Computer Networks and Communications |
| topics[1].display_name | Distributed Control Multi-Agent Systems |
| topics[2].id | https://openalex.org/T11106 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9016000032424927 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1711 |
| topics[2].subfield.display_name | Signal Processing |
| topics[2].display_name | Data Management and Algorithms |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.6472165584564209 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C87117476 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6371302604675293 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q362383 |
| concepts[1].display_name | Cardinality (data modeling) |
| concepts[2].id | https://openalex.org/C2775936607 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5571263432502747 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q466845 |
| concepts[2].display_name | Tracking (education) |
| concepts[3].id | https://openalex.org/C207390915 |
| concepts[3].level | 2 |
| concepts[3].score | 0.554542064666748 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1230525 |
| concepts[3].display_name | Divergence (linguistics) |
| concepts[4].id | https://openalex.org/C24590314 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5472058057785034 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q336038 |
| concepts[4].display_name | Wireless sensor network |
| concepts[5].id | https://openalex.org/C198082294 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5454358458518982 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q3399648 |
| concepts[5].display_name | Position (finance) |
| concepts[6].id | https://openalex.org/C16345878 |
| concepts[6].level | 2 |
| concepts[6].score | 0.5254382491111755 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q107472979 |
| concepts[6].display_name | Orientation (vector space) |
| concepts[7].id | https://openalex.org/C62611344 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4977417290210724 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q1062658 |
| concepts[7].display_name | Node (physics) |
| concepts[8].id | https://openalex.org/C141513077 |
| concepts[8].level | 3 |
| concepts[8].score | 0.45757412910461426 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q378542 |
| concepts[8].display_name | Independent and identically distributed random variables |
| concepts[9].id | https://openalex.org/C106131492 |
| concepts[9].level | 2 |
| concepts[9].score | 0.42788293957710266 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q3072260 |
| concepts[9].display_name | Filter (signal processing) |
| concepts[10].id | https://openalex.org/C113174947 |
| concepts[10].level | 2 |
| concepts[10].score | 0.4265751540660858 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q2859736 |
| concepts[10].display_name | Tree (set theory) |
| concepts[11].id | https://openalex.org/C11413529 |
| concepts[11].level | 1 |
| concepts[11].score | 0.37898170948028564 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[11].display_name | Algorithm |
| concepts[12].id | https://openalex.org/C33923547 |
| concepts[12].level | 0 |
| concepts[12].score | 0.2918851971626282 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[12].display_name | Mathematics |
| concepts[13].id | https://openalex.org/C122123141 |
| concepts[13].level | 2 |
| concepts[13].score | 0.2622487545013428 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q176623 |
| concepts[13].display_name | Random variable |
| concepts[14].id | https://openalex.org/C31972630 |
| concepts[14].level | 1 |
| concepts[14].score | 0.19807037711143494 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[14].display_name | Computer vision |
| concepts[15].id | https://openalex.org/C124101348 |
| concepts[15].level | 1 |
| concepts[15].score | 0.1585601270198822 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[15].display_name | Data mining |
| concepts[16].id | https://openalex.org/C105795698 |
| concepts[16].level | 1 |
| concepts[16].score | 0.08225774765014648 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[16].display_name | Statistics |
| concepts[17].id | https://openalex.org/C127413603 |
| concepts[17].level | 0 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[17].display_name | Engineering |
| concepts[18].id | https://openalex.org/C19417346 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q7922 |
| concepts[18].display_name | Pedagogy |
| concepts[19].id | https://openalex.org/C41895202 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q8162 |
| concepts[19].display_name | Linguistics |
| concepts[20].id | https://openalex.org/C31258907 |
| concepts[20].level | 1 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q1301371 |
| concepts[20].display_name | Computer network |
| concepts[21].id | https://openalex.org/C138885662 |
| concepts[21].level | 0 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[21].display_name | Philosophy |
| concepts[22].id | https://openalex.org/C134306372 |
| concepts[22].level | 1 |
| concepts[22].score | 0.0 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q7754 |
| concepts[22].display_name | Mathematical analysis |
| concepts[23].id | https://openalex.org/C10138342 |
| concepts[23].level | 1 |
| concepts[23].score | 0.0 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q43015 |
| concepts[23].display_name | Finance |
| concepts[24].id | https://openalex.org/C2524010 |
| concepts[24].level | 1 |
| concepts[24].score | 0.0 |
| concepts[24].wikidata | https://www.wikidata.org/wiki/Q8087 |
| concepts[24].display_name | Geometry |
| concepts[25].id | https://openalex.org/C66938386 |
| concepts[25].level | 1 |
| concepts[25].score | 0.0 |
| concepts[25].wikidata | https://www.wikidata.org/wiki/Q633538 |
| concepts[25].display_name | Structural engineering |
| concepts[26].id | https://openalex.org/C15744967 |
| concepts[26].level | 0 |
| concepts[26].score | 0.0 |
| concepts[26].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[26].display_name | Psychology |
| concepts[27].id | https://openalex.org/C162324750 |
| concepts[27].level | 0 |
| concepts[27].score | 0.0 |
| concepts[27].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[27].display_name | Economics |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.6472165584564209 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/cardinality |
| keywords[1].score | 0.6371302604675293 |
| keywords[1].display_name | Cardinality (data modeling) |
| keywords[2].id | https://openalex.org/keywords/tracking |
| keywords[2].score | 0.5571263432502747 |
| keywords[2].display_name | Tracking (education) |
| keywords[3].id | https://openalex.org/keywords/divergence |
| keywords[3].score | 0.554542064666748 |
| keywords[3].display_name | Divergence (linguistics) |
| keywords[4].id | https://openalex.org/keywords/wireless-sensor-network |
| keywords[4].score | 0.5472058057785034 |
| keywords[4].display_name | Wireless sensor network |
| keywords[5].id | https://openalex.org/keywords/position |
| keywords[5].score | 0.5454358458518982 |
| keywords[5].display_name | Position (finance) |
| keywords[6].id | https://openalex.org/keywords/orientation |
| keywords[6].score | 0.5254382491111755 |
| keywords[6].display_name | Orientation (vector space) |
| keywords[7].id | https://openalex.org/keywords/node |
| keywords[7].score | 0.4977417290210724 |
| keywords[7].display_name | Node (physics) |
| keywords[8].id | https://openalex.org/keywords/independent-and-identically-distributed-random-variables |
| keywords[8].score | 0.45757412910461426 |
| keywords[8].display_name | Independent and identically distributed random variables |
| keywords[9].id | https://openalex.org/keywords/filter |
| keywords[9].score | 0.42788293957710266 |
| keywords[9].display_name | Filter (signal processing) |
| keywords[10].id | https://openalex.org/keywords/tree |
| keywords[10].score | 0.4265751540660858 |
| keywords[10].display_name | Tree (set theory) |
| keywords[11].id | https://openalex.org/keywords/algorithm |
| keywords[11].score | 0.37898170948028564 |
| keywords[11].display_name | Algorithm |
| keywords[12].id | https://openalex.org/keywords/mathematics |
| keywords[12].score | 0.2918851971626282 |
| keywords[12].display_name | Mathematics |
| keywords[13].id | https://openalex.org/keywords/random-variable |
| keywords[13].score | 0.2622487545013428 |
| keywords[13].display_name | Random variable |
| keywords[14].id | https://openalex.org/keywords/computer-vision |
| keywords[14].score | 0.19807037711143494 |
| keywords[14].display_name | Computer vision |
| keywords[15].id | https://openalex.org/keywords/data-mining |
| keywords[15].score | 0.1585601270198822 |
| keywords[15].display_name | Data mining |
| keywords[16].id | https://openalex.org/keywords/statistics |
| keywords[16].score | 0.08225774765014648 |
| keywords[16].display_name | Statistics |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:1902.02523 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/1902.02523 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/1902.02523 |
| locations[1].id | doi:10.48550/arxiv.1902.02523 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.1902.02523 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5002775930 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-2871-9239 |
| authorships[0].author.display_name | Lin Gao |
| authorships[0].countries | IT |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I45084792 |
| authorships[0].affiliations[0].raw_affiliation_string | Dipartimento di Ingegneria dell'Informazione (DINFO) Università degli Studi di Firenze Florence Italy |
| authorships[0].institutions[0].id | https://openalex.org/I45084792 |
| authorships[0].institutions[0].ror | https://ror.org/04jr1s763 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I45084792 |
| authorships[0].institutions[0].country_code | IT |
| authorships[0].institutions[0].display_name | University of Florence |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Lin Gao |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Dipartimento di Ingegneria dell'Informazione (DINFO) Università degli Studi di Firenze Florence Italy |
| authorships[1].author.id | https://openalex.org/A5088425269 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-0124-4715 |
| authorships[1].author.display_name | Giorgio Battistelli |
| authorships[1].countries | IT |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I45084792 |
| authorships[1].affiliations[0].raw_affiliation_string | Dipartimento di Ingegneria dell'Informazione (DINFO) Università degli Studi di Firenze Florence Italy |
| authorships[1].institutions[0].id | https://openalex.org/I45084792 |
| authorships[1].institutions[0].ror | https://ror.org/04jr1s763 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I45084792 |
| authorships[1].institutions[0].country_code | IT |
| authorships[1].institutions[0].display_name | University of Florence |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Giorgio Battistelli |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Dipartimento di Ingegneria dell'Informazione (DINFO) Università degli Studi di Firenze Florence Italy |
| authorships[2].author.id | https://openalex.org/A5050723190 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-5049-3577 |
| authorships[2].author.display_name | Luigi Chisci |
| authorships[2].countries | IT |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I45084792 |
| authorships[2].affiliations[0].raw_affiliation_string | Dipartimento di Ingegneria dell'Informazione (DINFO) Università degli Studi di Firenze Florence Italy |
| authorships[2].institutions[0].id | https://openalex.org/I45084792 |
| authorships[2].institutions[0].ror | https://ror.org/04jr1s763 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I45084792 |
| authorships[2].institutions[0].country_code | IT |
| authorships[2].institutions[0].display_name | University of Florence |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Luigi Chisci |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Dipartimento di Ingegneria dell'Informazione (DINFO) Università degli Studi di Firenze Florence Italy |
| authorships[3].author.id | https://openalex.org/A5039556214 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-0384-9854 |
| authorships[3].author.display_name | Ping Wei |
| authorships[3].countries | CN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I150229711 |
| authorships[3].affiliations[0].raw_affiliation_string | [School of Information, and Communication Engineering, University of Electronic Science, and Technology of China, Chengdu, China] |
| authorships[3].institutions[0].id | https://openalex.org/I150229711 |
| authorships[3].institutions[0].ror | https://ror.org/04qr3zq92 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I150229711 |
| authorships[3].institutions[0].country_code | CN |
| authorships[3].institutions[0].display_name | University of Electronic Science and Technology of China |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Ping Wei |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | [School of Information, and Communication Engineering, University of Electronic Science, and Technology of China, Chengdu, China] |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/1902.02523 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Distributed Joint Sensor Registration and Multitarget Tracking Via Sensor Network |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10711 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9994999766349792 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Target Tracking and Data Fusion in Sensor Networks |
| related_works | https://openalex.org/W2002177687, https://openalex.org/W2058438338, https://openalex.org/W2019471580, https://openalex.org/W3004218185, https://openalex.org/W4390241083, https://openalex.org/W2941284322, https://openalex.org/W4245457074, https://openalex.org/W4224920876, https://openalex.org/W2168299207, https://openalex.org/W2323735050 |
| cited_by_count | 2 |
| counts_by_year[0].year | 2022 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2019 |
| counts_by_year[1].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:1902.02523 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/1902.02523 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/1902.02523 |
| primary_location.id | pmh:oai:arXiv.org:1902.02523 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/1902.02523 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/1902.02523 |
| publication_date | 2019-02-07 |
| publication_year | 2019 |
| referenced_works | https://openalex.org/W2078742450, https://openalex.org/W2140242774, https://openalex.org/W2111715002, https://openalex.org/W2100688788, https://openalex.org/W2526368751, https://openalex.org/W2894226520, https://openalex.org/W2165930472, https://openalex.org/W2901168609, https://openalex.org/W652333456, https://openalex.org/W2122994915, https://openalex.org/W2761761724, https://openalex.org/W2588209989, https://openalex.org/W2093727232, https://openalex.org/W34992941, https://openalex.org/W1983838955, https://openalex.org/W2142300547, https://openalex.org/W1984526963, https://openalex.org/W1820162952, https://openalex.org/W1970916773, https://openalex.org/W2762588164, https://openalex.org/W1994684794, https://openalex.org/W2126885789, https://openalex.org/W2040398233, https://openalex.org/W2137585588, https://openalex.org/W2110407935, https://openalex.org/W217460636, https://openalex.org/W2160643434, https://openalex.org/W2293128770, https://openalex.org/W2045834636, https://openalex.org/W2049244691, https://openalex.org/W1988543519, https://openalex.org/W2145122884, https://openalex.org/W2789551723, https://openalex.org/W2161435744, https://openalex.org/W2150843948, https://openalex.org/W1997942227, https://openalex.org/W2162814504, https://openalex.org/W2130326036, https://openalex.org/W2092323252, https://openalex.org/W2106360727, https://openalex.org/W2106873007, https://openalex.org/W1844818070, https://openalex.org/W2105905583, https://openalex.org/W2484753449, https://openalex.org/W2024522552 |
| referenced_works_count | 45 |
| abstract_inverted_index.a | 6, 21, 66, 90, 124 |
| abstract_inverted_index.In | 121 |
| abstract_inverted_index.an | 54 |
| abstract_inverted_index.as | 34, 41, 53, 158, 160 |
| abstract_inverted_index.in | 20, 82, 101 |
| abstract_inverted_index.is | 51, 74, 107, 136, 145 |
| abstract_inverted_index.no | 26 |
| abstract_inverted_index.of | 5, 16, 44, 103, 141 |
| abstract_inverted_index.on | 150 |
| abstract_inverted_index.to | 33, 40, 79, 111 |
| abstract_inverted_index.RFS | 87 |
| abstract_inverted_index.The | 48 |
| abstract_inverted_index.and | 37, 56, 65, 114, 133, 154, 164 |
| abstract_inverted_index.for | 9, 117, 129 |
| abstract_inverted_index.its | 45 |
| abstract_inverted_index.run | 75 |
| abstract_inverted_index.set | 50, 63 |
| abstract_inverted_index.the | 17, 29, 77, 85, 95, 98, 112, 139, 142 |
| abstract_inverted_index.Each | 12 |
| abstract_inverted_index.Then | 89 |
| abstract_inverted_index.This | 0 |
| abstract_inverted_index.both | 151, 162 |
| abstract_inverted_index.cost | 92 |
| abstract_inverted_index.each | 83 |
| abstract_inverted_index.gets | 14 |
| abstract_inverted_index.node | 84 |
| abstract_inverted_index.over | 76 |
| abstract_inverted_index.this | 122 |
| abstract_inverted_index.tree | 152 |
| abstract_inverted_index.way, | 123 |
| abstract_inverted_index.well | 159 |
| abstract_inverted_index.with | 109, 156, 161 |
| abstract_inverted_index.about | 28 |
| abstract_inverted_index.drift | 35, 113 |
| abstract_inverted_index.joint | 130 |
| abstract_inverted_index.local | 22, 99 |
| abstract_inverted_index.paper | 1 |
| abstract_inverted_index.terms | 102 |
| abstract_inverted_index.(CPHD) | 72 |
| abstract_inverted_index.(RFS), | 64 |
| abstract_inverted_index.filter | 73 |
| abstract_inverted_index.finite | 62 |
| abstract_inverted_index.frame, | 24 |
| abstract_inverted_index.having | 25 |
| abstract_inverted_index.linear | 163 |
| abstract_inverted_index.nodes. | 47 |
| abstract_inverted_index.random | 61 |
| abstract_inverted_index.sensor | 7, 13, 118, 131 |
| abstract_inverted_index.target | 18 |
| abstract_inverted_index.between | 97 |
| abstract_inverted_index.cluster | 60 |
| abstract_inverted_index.compute | 81 |
| abstract_inverted_index.cycles, | 157 |
| abstract_inverted_index.density | 71 |
| abstract_inverted_index.modeled | 52 |
| abstract_inverted_index.network | 8, 78 |
| abstract_inverted_index.respect | 110 |
| abstract_inverted_index.through | 147 |
| abstract_inverted_index.(i.i.d.) | 59 |
| abstract_inverted_index.Finally, | 138 |
| abstract_inverted_index.approach | 128, 144 |
| abstract_inverted_index.averaged | 104 |
| abstract_inverted_index.azimuths | 38 |
| abstract_inverted_index.density. | 88 |
| abstract_inverted_index.devised. | 137 |
| abstract_inverted_index.feasible | 126 |
| abstract_inverted_index.networks | 153, 155 |
| abstract_inverted_index.position | 19 |
| abstract_inverted_index.proposed | 143 |
| abstract_inverted_index.relative | 30 |
| abstract_inverted_index.sensors. | 166 |
| abstract_inverted_index.suitable | 91 |
| abstract_inverted_index.tracking | 135 |
| abstract_inverted_index.(referred | 32, 39 |
| abstract_inverted_index.addresses | 2 |
| abstract_inverted_index.consensus | 67 |
| abstract_inverted_index.function, | 93 |
| abstract_inverted_index.knowledge | 27 |
| abstract_inverted_index.minimized | 108 |
| abstract_inverted_index.nonlinear | 165 |
| abstract_inverted_index.positions | 31 |
| abstract_inverted_index.posterior | 86 |
| abstract_inverted_index.purposes. | 120 |
| abstract_inverted_index.tracking. | 11 |
| abstract_inverted_index.xpressing | 94 |
| abstract_inverted_index.coordinate | 23 |
| abstract_inverted_index.hypothesis | 70 |
| abstract_inverted_index.parameters | 116 |
| abstract_inverted_index.posteriors | 100 |
| abstract_inverted_index.simulation | 148 |
| abstract_inverted_index.cardinality | 68 |
| abstract_inverted_index.discrepancy | 96 |
| abstract_inverted_index.distributed | 3, 58 |
| abstract_inverted_index.divergence, | 106 |
| abstract_inverted_index.experiments | 149 |
| abstract_inverted_index.identically | 57 |
| abstract_inverted_index.independent | 55 |
| abstract_inverted_index.multitarget | 10, 49, 134 |
| abstract_inverted_index.neighboring | 46 |
| abstract_inverted_index.orientation | 42, 115 |
| abstract_inverted_index.parameters) | 36, 43 |
| abstract_inverted_index.probability | 69 |
| abstract_inverted_index.recursively | 80 |
| abstract_inverted_index.registraton | 132 |
| abstract_inverted_index.demonstrated | 146 |
| abstract_inverted_index.measurements | 15 |
| abstract_inverted_index.optimization | 127 |
| abstract_inverted_index.registration | 4, 119 |
| abstract_inverted_index.effectiveness | 140 |
| abstract_inverted_index.computationally | 125 |
| abstract_inverted_index.Kullback-Leibler | 105 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile |