Collaborative Trajectory Optimization for Multitarget Tracking in Airborne Radar Network With Missing Data

In this paper, an effective collaborative trajectory optimization (CTO) strategy is proposed for multitarget tracking in airborne radar networks with missing data. Missing data may occur during data exchange between radar nodes and a fusion center (FC) due to unreliability of communication channels....

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on signal processing Vol. 73; pp. 1048 - 1064
Main Authors Hu, Juan, Zuo, Lei, Varshney, Pramod K., Lan, Zhengyu, Gao, Yongchan
Format Journal Article
LanguageEnglish
Published New York IEEE 2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Airborne radar
airborne radar network
Approximation
Atmospheric modeling
Collaboration
Collision avoidance
Data exchange
Lower bounds
Missing data
Multiple target tracking
Optimization
Radar
Radar cross-sections
Radar data
Radar networks
Radar tracking
Simulation
Symbols
Target tracking
Tracking
Trajectory optimization
Online AccessGet full text
ISSN1053-587X
1941-0476
DOI10.1109/TSP.2025.3540798

Cover

Abstract In this paper, an effective collaborative trajectory optimization (CTO) strategy is proposed for multitarget tracking in airborne radar networks with missing data. Missing data may occur during data exchange between radar nodes and a fusion center (FC) due to unreliability of communication channels. The CTO strategy aims to enhance the overall multi-target tracking performance by collaboratively optimizing the trajectories of airborne radars and the FC. In this paper, we derive the posterior Cramér-Rao lower bound (PCRLB) with missing data to evaluate the target tracking performance. On this basis, to maximize the target tracking performance while considering dynamics, collision avoidance, and communication distance constraints, we formulate the CTO optimization problem. The formulated problem is non-convex and internally coupled, which is challenging to solve directly. We decompose the CTO problem into two subproblems and devise an alternating optimization method. Specifically, approximation, and successive convex approximation are applied to make the subproblems solvable. Then, the two subproblems are solved alternately to realize the collaborative trajectory optimization of radars and the FC. Simulation results demonstrate that the proposed CTO strategy achieves better target tracking performance as compared with other benchmark strategies.
AbstractList In this paper, an effective collaborative trajectory optimization (CTO) strategy is proposed for multitarget tracking in airborne radar networks with missing data. Missing data may occur during data exchange between radar nodes and a fusion center (FC) due to unreliability of communication channels. The CTO strategy aims to enhance the overall multi-target tracking performance by collaboratively optimizing the trajectories of airborne radars and the FC. In this paper, we derive the posterior Cramér-Rao lower bound (PCRLB) with missing data to evaluate the target tracking performance. On this basis, to maximize the target tracking performance while considering dynamics, collision avoidance, and communication distance constraints, we formulate the CTO optimization problem. The formulated problem is non-convex and internally coupled, which is challenging to solve directly. We decompose the CTO problem into two subproblems and devise an alternating optimization method. Specifically, approximation, and successive convex approximation are applied to make the subproblems solvable. Then, the two subproblems are solved alternately to realize the collaborative trajectory optimization of radars and the FC. Simulation results demonstrate that the proposed CTO strategy achieves better target tracking performance as compared with other benchmark strategies.
Author Hu, Juan
Zuo, Lei
Lan, Zhengyu
Gao, Yongchan
Varshney, Pramod K.
Author_xml – sequence: 1
  givenname: Juan
  orcidid: 0000-0003-0671-0153
  surname: Hu
  fullname: Hu, Juan
  email: jhu24@stu.xidian.edu.cn
  organization: National Key Laboratory of Radar Signal Processing, Xidian University, Xi'an, China
– sequence: 2
  givenname: Lei
  orcidid: 0000-0002-7478-3648
  surname: Zuo
  fullname: Zuo, Lei
  email: lzuo@mail.xidian.edu.cn
  organization: National Key Laboratory of Radar Signal Processing, Xidian University, Xi'an, China
– sequence: 3
  givenname: Pramod K.
  orcidid: 0000-0003-4504-5088
  surname: Varshney
  fullname: Varshney, Pramod K.
  email: varshney@syr.edu
  organization: Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, USA
– sequence: 4
  givenname: Zhengyu
  orcidid: 0000-0001-5173-167X
  surname: Lan
  fullname: Lan, Zhengyu
  email: lanzhengyu@stu.xidian.edu.cn
  organization: National Key Laboratory of Radar Signal Processing, Xidian University, Xi'an, China
– sequence: 5
  givenname: Yongchan
  orcidid: 0000-0002-9735-5224
  surname: Gao
  fullname: Gao, Yongchan
  email: ycgao@xidian.edu.cn
  organization: School of Electronic Engineering, Xidian University, Xi'an, China
BookMark eNpNkD1PwzAQhi0EEhTYGRgsMaf4EjtOxqp8SuVDUARbdHEuxWkbF8cFwa8nVRmY7tXpee-kZ8B2W9cSYycghgAiP58-Pw5jEathoqTQebbDDiCXEAmp090-C5VEKtNv-2zQdY0QIGWeHrBm7BYLLJ3HYD-JTz02ZILz3_xhFezS_vR71_LaeX63XgQb0M8obDgzt-2M25aPrO_7LfEnrNDzewpfzs_5qw3v_M523Qa7wIBHbK_GRUfHf_OQvVxdTsc30eTh-nY8mkQGtAoRkUFJMdUmN2WWllhrkqAxRh1XZZIi5KBrrdBUFWnMjZClRKkUQJbqTCSH7Gx7d-Xdx5q6UDRu7dv-ZZGAjpNYJTH0lNhSxruu81QXK2-X6L8LEMXGaNEbLTZGiz-jfeV0W7FE9A_PMgGgkl9Lv3YB
CODEN ITPRED
Cites_doi 10.1109/JSYST.2021.3116020
10.1109/TAES.2015.140044
10.1109/TAES.2007.4285352
10.1109/MAES.2021.3052312
10.1109/TWC.2023.3304900
10.1016/j.sigpro.2023.108973
10.1109/TGRS.2020.2998814
10.1109/TAES.2019.2949384
10.1109/TGRS.2023.3239952
10.1109/TSP.2024.3352915
10.1109/TAC.2008.921012
10.1016/j.automatica.2016.01.061
10.1109/JSEN.2011.2167964
10.1016/j.sigpro.2022.108689
10.1109/TAES.2024.3368378
10.1109/TSP.2016.2573767
10.1109/cec.2005.1554897
10.1109/TSP.2021.3101018
10.1109/TAES.2021.3138869
10.1109/TIT.1969.1054329
10.1109/ICECS.2018.8617880
10.1109/TSP.2023.3265882
10.1109/SAHCN.2004.1381954
10.1109/TAC.2017.2781374
10.1109/ICT.2018.8464879
10.1109/78.668800
10.1109/COMST.2021.3103044
10.1109/JIOT.2022.3233576
10.1109/CISDA.2009.5356539
10.1109/TAES.2024.3367662
10.1109/TSP.2021.3051743
10.1109/TAC.2004.834121
10.1109/INFCOM.2010.5461926
10.1201/9781439883136-12
10.1080/03081087.2014.891588
10.1109/JPROC.2006.887306
10.1109/LCOMM.2018.2849718
10.1109/MAES.2019.2957847
10.1109/RADAR.2008.4720926
10.1109/9780470544198
10.1109/TAES.2023.3328799
10.1109/MSP.2018.2822847
ContentType Journal Article
Copyright Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2025
Copyright_xml – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2025
DBID 97E
RIA
RIE
AAYXX
CITATION
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
DOI 10.1109/TSP.2025.3540798
DatabaseName IEEE All-Society Periodicals Package (ASPP) 2005–Present
IEEE All-Society Periodicals Package (ASPP) 1998–Present
IEEE Electronic Library (IEL)
CrossRef
Computer and Information Systems Abstracts
Electronics & Communications Abstracts
Technology Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
DatabaseTitle CrossRef
Technology Research Database
Computer and Information Systems Abstracts – Academic
Electronics & Communications Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts Professional
DatabaseTitleList
Technology Research Database
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE/IET Electronic Library
  url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1941-0476
EndPage 1064
ExternalDocumentID 10_1109_TSP_2025_3540798
10880115
Genre orig-research
GrantInformation_xml – fundername: National Natural Science Foundation of China
  grantid: 62371379; 62371447
  funderid: 10.13039/501100001809
GroupedDBID -~X
.DC
0R~
29I
3EH
4.4
53G
5GY
5VS
6IK
85S
97E
AAJGR
AARMG
AASAJ
AAWTH
ABAZT
ABFSI
ABQJQ
ABVLG
ACGFO
ACIWK
ACKIV
ACNCT
AENEX
AETIX
AGQYO
AGSQL
AHBIQ
AI.
AIBXA
AJQPL
AKJIK
AKQYR
ALLEH
ALMA_UNASSIGNED_HOLDINGS
ASUFR
ATWAV
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CS3
E.L
EBS
EJD
F5P
HZ~
H~9
ICLAB
IFIPE
IFJZH
IPLJI
JAVBF
LAI
MS~
O9-
OCL
P2P
RIA
RIE
RNS
TAE
TN5
VH1
AAYOK
AAYXX
CITATION
RIG
7SC
7SP
8FD
JQ2
L7M
L~C
L~D
ID FETCH-LOGICAL-c175t-eeca4e2efc9cb86baf7e417a2a72db36a1917f75acdde7a9c04b4a45511867803
IEDL.DBID RIE
ISSN 1053-587X
IngestDate Tue Jul 22 18:41:23 EDT 2025
Tue Jul 01 05:25:41 EDT 2025
Wed Aug 27 01:49:28 EDT 2025
IsPeerReviewed true
IsScholarly true
Language English
License https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html
https://doi.org/10.15223/policy-029
https://doi.org/10.15223/policy-037
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c175t-eeca4e2efc9cb86baf7e417a2a72db36a1917f75acdde7a9c04b4a45511867803
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0003-4504-5088
0000-0001-5173-167X
0000-0002-7478-3648
0000-0002-9735-5224
0000-0003-0671-0153
PQID 3172325321
PQPubID 85478
PageCount 17
ParticipantIDs proquest_journals_3172325321
ieee_primary_10880115
crossref_primary_10_1109_TSP_2025_3540798
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 20250000
2025-00-00
20250101
PublicationDateYYYYMMDD 2025-01-01
PublicationDate_xml – year: 2025
  text: 20250000
PublicationDecade 2020
PublicationPlace New York
PublicationPlace_xml – name: New York
PublicationTitle IEEE transactions on signal processing
PublicationTitleAbbrev TSP
PublicationYear 2025
Publisher IEEE
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml – name: IEEE
– name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References ref13
ref35
ref12
ref34
ref15
ref37
ref14
ref36
ref31
ref30
ref11
ref33
ref10
ref32
ref2
ref1
ref17
ref39
ref16
ref38
ref19
ref18
ref24
ref23
ref26
ref25
ref20
ref42
ref41
ref22
Boyd (ref44) 2013
ref21
ref28
Gunawan (ref43) 2002; 55
ref27
ref29
ref8
ref7
ref9
ref4
ref3
ref6
ref5
ref40
References_xml – ident: ref15
  doi: 10.1109/JSYST.2021.3116020
– ident: ref32
  doi: 10.1109/TAES.2015.140044
– ident: ref40
  doi: 10.1109/TAES.2007.4285352
– ident: ref3
  doi: 10.1109/MAES.2021.3052312
– ident: ref26
  doi: 10.1109/TWC.2023.3304900
– ident: ref29
  doi: 10.1016/j.sigpro.2023.108973
– ident: ref10
  doi: 10.1109/TGRS.2020.2998814
– ident: ref11
  doi: 10.1109/TAES.2019.2949384
– ident: ref14
  doi: 10.1109/TGRS.2023.3239952
– ident: ref28
  doi: 10.1109/TSP.2024.3352915
– ident: ref21
  doi: 10.1109/TAC.2008.921012
– ident: ref23
  doi: 10.1016/j.automatica.2016.01.061
– ident: ref4
  doi: 10.1109/JSEN.2011.2167964
– ident: ref8
  doi: 10.1016/j.sigpro.2022.108689
– ident: ref9
  doi: 10.1109/TAES.2024.3368378
– year: 2013
  ident: ref44
  article-title: Convex Optimization
– ident: ref5
  doi: 10.1109/TSP.2016.2573767
– ident: ref12
  doi: 10.1109/cec.2005.1554897
– ident: ref38
  doi: 10.1109/TSP.2021.3101018
– ident: ref39
  doi: 10.1109/TAES.2021.3138869
– volume: 55
  start-page: 53
  issue: 1
  year: 2002
  ident: ref43
  article-title: On n-inner products, n-norms, and the Cauchy–Schwarz inequality
  publication-title: Sci. Math. Japn.
– ident: ref19
  doi: 10.1109/TIT.1969.1054329
– ident: ref36
  doi: 10.1109/ICECS.2018.8617880
– ident: ref13
  doi: 10.1109/TSP.2023.3265882
– ident: ref25
  doi: 10.1109/SAHCN.2004.1381954
– ident: ref24
  doi: 10.1109/TAC.2017.2781374
– ident: ref37
  doi: 10.1109/ICT.2018.8464879
– ident: ref30
  doi: 10.1109/78.668800
– ident: ref33
  doi: 10.1109/COMST.2021.3103044
– ident: ref27
  doi: 10.1109/JIOT.2022.3233576
– ident: ref41
  doi: 10.1109/CISDA.2009.5356539
– ident: ref7
  doi: 10.1109/TAES.2024.3367662
– ident: ref18
  doi: 10.1109/TSP.2021.3051743
– ident: ref20
  doi: 10.1109/TAC.2004.834121
– ident: ref17
  doi: 10.1109/INFCOM.2010.5461926
– ident: ref34
  doi: 10.1201/9781439883136-12
– ident: ref42
  doi: 10.1080/03081087.2014.891588
– ident: ref22
  doi: 10.1109/JPROC.2006.887306
– ident: ref35
  doi: 10.1109/LCOMM.2018.2849718
– ident: ref2
  doi: 10.1109/MAES.2019.2957847
– ident: ref6
  doi: 10.1109/RADAR.2008.4720926
– ident: ref31
  doi: 10.1109/9780470544198
– ident: ref16
  doi: 10.1109/TAES.2023.3328799
– ident: ref1
  doi: 10.1109/MSP.2018.2822847
SSID ssj0014496
Score 2.4646897
Snippet In this paper, an effective collaborative trajectory optimization (CTO) strategy is proposed for multitarget tracking in airborne radar networks with missing...
SourceID proquest
crossref
ieee
SourceType Aggregation Database
Index Database
Publisher
StartPage 1048
SubjectTerms Airborne radar
airborne radar network
Approximation
Atmospheric modeling
Collaboration
Collision avoidance
Data exchange
Lower bounds
Missing data
Multiple target tracking
Optimization
Radar
Radar cross-sections
Radar data
Radar networks
Radar tracking
Simulation
Symbols
Target tracking
Tracking
Trajectory optimization
Title Collaborative Trajectory Optimization for Multitarget Tracking in Airborne Radar Network With Missing Data
URI https://ieeexplore.ieee.org/document/10880115
https://www.proquest.com/docview/3172325321
Volume 73
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LT8MwDI5gJzjwHGIwUA5cOHSkbdKkx2kwTUgMxEPsVqWpKwaioNEhwa_HSTsYICRuPThVFDv2Z8cPQg4iUCrPBPMUGOHxiBkvznPtgYjiQDGVx67P7NkwGtzw05EY1cXqrhYGAFzyGXTsp3vLz57M1IbK8IajtPm2pHwRPbeqWOvzyYBzN4wL8ULoCSVHszdJFh9dX12gJxiIjg1yyFh9s0FuqMovTezMS3-VDGcbq7JKHjrTMu2Y9x89G_-98zWyUgNN2q0kY50sQLFBlufaD26S-96XELwCRbN172L4b_QcFcljXaFJEdbSqk7XZY1bOmMD7HRc0O54gusLoJc60xM6rJLK6e24vKNnyFNLdqxL3SQ3_ZPr3sCrZy94BgFF6QEYzSGA3MQmVVGqcwnclzrQMsjSMNLWz8ul0Ab1o9SxYTzlmgvrsKD9Y-EWaRRPBWwTigAPjAwi42c-F6FRPgMlM24YM6hwshY5nHEjea5abCTONWFxgpxLLOeSmnMt0rSHO0dXnWuLtGf8S-pL-JIgNEK8KMLA3_lj2S5Zsn-vQipt0ignU9hDkFGm-064PgCHec-N
linkProvider IEEE
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LT8MwDI4QHIADb8R45sCFQ0faJk16RDw0HhsIhtitSlNXDERBo0OCX4-TdjyFxK0HR43yOfYXx3YI2Y5AqTwTzFNghMcjZrw4z7UHIooDxVQeuz6z7U7UuuYnPdGri9VdLQwAuOQzaNpPd5efPZqhDZXhDkdt821J-QQ6fuFX5Voflwacu-e4kDGEnlCyN7qVZPFu9-oCz4KBaNowh4zVNy_knlX5ZYudgzmaJZ3R1Kq8kvvmsEyb5u1H18Z_z32OzNRUk-5VujFPxqBYINNfGhAukrv9TzV4AYqO685F8V_pOZqSh7pGkyKxpVWlrssbt3LGhthpv6B7_QGOL4Be6kwPaKdKK6c3_fKWthFVK3agS71Ero8Ou_str359wTNIKUoPwGgOAeQmNqmKUp1L4L7UgZZBloaRtie9XApt0EJKHRvGU64tLLZHnmLhMhkvHgtYIRQpHhgZRMbPfC5Co3wGSmbcMGbQ5GQNsjNCI3mqmmwk7nDC4gSRSyxySY1cgyzZxf0iV61rg6yP8EvqbficIDlCxijCwF_9Y9gWmWx122fJ2XHndI1M2T9VAZZ1Ml4OhrCBlKNMN52ivQOE9dLW
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Collaborative+Trajectory+Optimization+for+Multitarget+Tracking+in+Airborne+Radar+Network+With+Missing+Data&rft.jtitle=IEEE+transactions+on+signal+processing&rft.au=Hu%2C+Juan&rft.au=Zuo%2C+Lei&rft.au=Varshney%2C+Pramod+K.&rft.au=Lan%2C+Zhengyu&rft.date=2025&rft.issn=1053-587X&rft.eissn=1941-0476&rft.volume=73&rft.spage=1048&rft.epage=1064&rft_id=info:doi/10.1109%2FTSP.2025.3540798&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_TSP_2025_3540798
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1053-587X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1053-587X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1053-587X&client=summon