Weighted maximum mixture complex correntropy-based past algorithm: a novel approach for low-altitude target parameter estimation.
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| Title: | Weighted maximum mixture complex correntropy-based past algorithm: a novel approach for low-altitude target parameter estimation. |
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| Authors: | Li, Li1 (AUTHOR) ffsimple@163.com, Qiu, Tianshuang2 (AUTHOR) qiutsh@dlut.edu.cn |
| Source: | Ain Shams Engineering Journal. Apr2026, Vol. 17 Issue 4, pN.PAG-N.PAG. 1p. |
| Subjects: | Parameter estimation, Radar signal processing, Subspace identification (Mathematics), Random noise theory, Robust statistics, Signal detection |
| Abstract: | Aiming at the challenges of strong ground clutter interference, low signal-to-noise ratio, and near-field non-stationary signals in detecting low, slow, and small (LSS) targets in low-altitude environments, this paper proposes a joint parameter estimation method for low-altitude targets based on an improved weighted maximum mixture complex correntropy-based projection approximation subspace tracking (WMMCC-PAST) algorithm. Initially, an innovatively developed weighted mixture complex correntropy function integrates complex Gaussian kernels with a dynamic weighting mechanism. This approach effectively addresses the limitations of traditional correntropy methods in suppressing continuous similar-amplitude noise, overcoming fixed kernel bandwidth constraints, and limited adaptability of single-kernel approaches, thereby markedly enhancing the algorithm's robustness in complex noise environments. Subsequently, a cost function based on the WMMCC criterion is constructed, integrating the weighted maximum mixture correntropy criterion with the PAST algorithm framework. By embedding the robust correntropy-based metric into the subspace tracking process, this formulation significantly improves the algorithm's resilience to heavy-tailed noise commonly encountered in low-altitude radar scenarios. Next, this work theoretically derives and implements a robust WMMCC-PAST algorithm tailored for impulsive noise environments, which significantly improves tracking performance in low-altitude radar applications affected by non-Gaussian disturbances, particularly under heavy-tailed noise conditions. Furthermore, theoretical analysis establishes the boundedness of the proposed weighted mixture complex correntropy function, proves the convergence of the WMMCC-PAST algorithm, and further examines its robustness under α-stable noise. In addition, the computational complexity and its practical relevance to radar applications are analyzed to support the feasibility of real-time deployment. Experimental results demonstrate that the proposed algorithm has good estimation performance. This study provides an effective technical solution for LSS target detection in low-altitude security fields, holding significant theoretical value and promising engineering applications. [ABSTRACT FROM AUTHOR] |
| Copyright of Ain Shams Engineering Journal is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 192509718 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Weighted maximum mixture complex correntropy-based past algorithm: a novel approach for low-altitude target parameter estimation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Li%22">Li, Li</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ffsimple@163.com</i><br /><searchLink fieldCode="AR" term="%22Qiu%2C+Tianshuang%22">Qiu, Tianshuang</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> qiutsh@dlut.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Ain+Shams+Engineering+Journal%22">Ain Shams Engineering Journal</searchLink>. Apr2026, Vol. 17 Issue 4, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Radar+signal+processing%22">Radar signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Subspace+identification+%28Mathematics%29%22">Subspace identification (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Random+noise+theory%22">Random noise theory</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+statistics%22">Robust statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+detection%22">Signal detection</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Aiming at the challenges of strong ground clutter interference, low signal-to-noise ratio, and near-field non-stationary signals in detecting low, slow, and small (LSS) targets in low-altitude environments, this paper proposes a joint parameter estimation method for low-altitude targets based on an improved weighted maximum mixture complex correntropy-based projection approximation subspace tracking (WMMCC-PAST) algorithm. Initially, an innovatively developed weighted mixture complex correntropy function integrates complex Gaussian kernels with a dynamic weighting mechanism. This approach effectively addresses the limitations of traditional correntropy methods in suppressing continuous similar-amplitude noise, overcoming fixed kernel bandwidth constraints, and limited adaptability of single-kernel approaches, thereby markedly enhancing the algorithm's robustness in complex noise environments. Subsequently, a cost function based on the WMMCC criterion is constructed, integrating the weighted maximum mixture correntropy criterion with the PAST algorithm framework. By embedding the robust correntropy-based metric into the subspace tracking process, this formulation significantly improves the algorithm's resilience to heavy-tailed noise commonly encountered in low-altitude radar scenarios. Next, this work theoretically derives and implements a robust WMMCC-PAST algorithm tailored for impulsive noise environments, which significantly improves tracking performance in low-altitude radar applications affected by non-Gaussian disturbances, particularly under heavy-tailed noise conditions. Furthermore, theoretical analysis establishes the boundedness of the proposed weighted mixture complex correntropy function, proves the convergence of the WMMCC-PAST algorithm, and further examines its robustness under α-stable noise. In addition, the computational complexity and its practical relevance to radar applications are analyzed to support the feasibility of real-time deployment. Experimental results demonstrate that the proposed algorithm has good estimation performance. This study provides an effective technical solution for LSS target detection in low-altitude security fields, holding significant theoretical value and promising engineering applications. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Ain Shams Engineering Journal is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.asej.2026.104078 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Parameter estimation Type: general – SubjectFull: Radar signal processing Type: general – SubjectFull: Subspace identification (Mathematics) Type: general – SubjectFull: Random noise theory Type: general – SubjectFull: Robust statistics Type: general – SubjectFull: Signal detection Type: general Titles: – TitleFull: Weighted maximum mixture complex correntropy-based past algorithm: a novel approach for low-altitude target parameter estimation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Li – PersonEntity: Name: NameFull: Qiu, Tianshuang IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20904479 Numbering: – Type: volume Value: 17 – Type: issue Value: 4 Titles: – TitleFull: Ain Shams Engineering Journal Type: main |
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