LPI-constrained collaborative transmit beampattern optimization and resource allocation for maneuvering targets tracking in colocated MIMO radar network
•This work addresses a low probability of intercept (LPI) constrained collaborative beampattern optimization and resource allocation (LPI-CBORA) for multiple maneuvering targets tracking (MMTT) in the colocated MIMO radar network.•In the proposed LPI-CBORA problem for maneuvering targets tracking, t...
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| Veröffentlicht in: | Signal processing Jg. 207; S. 108935 |
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01.06.2023
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| Abstract | •This work addresses a low probability of intercept (LPI) constrained collaborative beampattern optimization and resource allocation (LPI-CBORA) for multiple maneuvering targets tracking (MMTT) in the colocated MIMO radar network.•In the proposed LPI-CBORA problem for maneuvering targets tracking, the LPI is achieved via adaptively controlling the distribution of the transmit energy in the airspace for the first time.•We formulate the LPI-CBORA as a nonconvex optimization problem, where the node-target assignment, beampattern design and bandwidth allocation are collaboratively considered for the first time.•A two-stage solution algorithm incorporating with the successive convex approximation and the cyclic minimization algorithm is proposed to solve the LPI-CBORA-related problem efficiently.
Considering tracking multiple maneuvering targets with the presence of a hostile interceptor in the modern electronic warfare (EW) environment, how to maximize targets tracking performance while ensuring system’s anti-interception capability is of essential significance for the radar network consisting of multiple colocated MIMO radar (CMR) nodes. In this paper, we propose a novel low probability of intercept (LPI) constrained collaborative beampattern optimization and resource allocation (LPI-CBORA) strategy for multiple maneuvering targets tracking (MMTT) in the CMR network (CMRN). More precisely, the LPI-CBORA strategy is formulated as a nonconvex optimization problem, where the node-target assignment, beampattern design and bandwidth allocation are collaboratively considered for the first time. To tackle the nonconvex problem effectively, an efficient two-stage solution algorithm incorporating with the successive convex approximation (SCA) and the cyclic minimization algorithm (CMA) is developed. Numerical simulations are provided to verify the effectiveness and superiority of the proposed LPI-CBORA strategy. |
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| AbstractList | •This work addresses a low probability of intercept (LPI) constrained collaborative beampattern optimization and resource allocation (LPI-CBORA) for multiple maneuvering targets tracking (MMTT) in the colocated MIMO radar network.•In the proposed LPI-CBORA problem for maneuvering targets tracking, the LPI is achieved via adaptively controlling the distribution of the transmit energy in the airspace for the first time.•We formulate the LPI-CBORA as a nonconvex optimization problem, where the node-target assignment, beampattern design and bandwidth allocation are collaboratively considered for the first time.•A two-stage solution algorithm incorporating with the successive convex approximation and the cyclic minimization algorithm is proposed to solve the LPI-CBORA-related problem efficiently.
Considering tracking multiple maneuvering targets with the presence of a hostile interceptor in the modern electronic warfare (EW) environment, how to maximize targets tracking performance while ensuring system’s anti-interception capability is of essential significance for the radar network consisting of multiple colocated MIMO radar (CMR) nodes. In this paper, we propose a novel low probability of intercept (LPI) constrained collaborative beampattern optimization and resource allocation (LPI-CBORA) strategy for multiple maneuvering targets tracking (MMTT) in the CMR network (CMRN). More precisely, the LPI-CBORA strategy is formulated as a nonconvex optimization problem, where the node-target assignment, beampattern design and bandwidth allocation are collaboratively considered for the first time. To tackle the nonconvex problem effectively, an efficient two-stage solution algorithm incorporating with the successive convex approximation (SCA) and the cyclic minimization algorithm (CMA) is developed. Numerical simulations are provided to verify the effectiveness and superiority of the proposed LPI-CBORA strategy. |
| ArticleNumber | 108935 |
| Author | Cheng, Ting He, Zishu Su, Yang |
| Author_xml | – sequence: 1 givenname: Yang surname: Su fullname: Su, Yang – sequence: 2 givenname: Ting orcidid: 0000-0003-1922-8083 surname: Cheng fullname: Cheng, Ting email: citrus@uestc.edu.cn – sequence: 3 givenname: Zishu surname: He fullname: He, Zishu |
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| Cites_doi | 10.1016/j.inffus.2022.06.009 10.1049/rsn2.12026 10.1109/TAP.2010.2052573 10.1016/j.sigpro.2021.108374 10.1109/TAES.2003.1261132 10.1109/TAES.2021.3138869 10.1109/TSP.2013.2252173 10.1109/LSP.2021.3108675 10.1109/7.640267 10.1109/TSP.2020.2976587 10.1109/TSP.2021.3101018 10.1109/TSP.2015.2417504 10.1109/TVT.2020.3002899 |
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| Keywords | Beampattern optimization Low probability of intercept (LPI) Successive convex approximation (SCA) Radar network Cyclic minimization algorithm (CMA) Resource allocation |
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| SubjectTerms | Beampattern optimization Cyclic minimization algorithm (CMA) Low probability of intercept (LPI) Radar network Resource allocation Successive convex approximation (SCA) |
| Title | LPI-constrained collaborative transmit beampattern optimization and resource allocation for maneuvering targets tracking in colocated MIMO radar network |
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