A Hybrid Integration and Parameter Estimation Algorithm Based on KTSMF for Sea-Surface Moving Targets Using Space-Based Bistatic Passive Radar.
Saved in:
| Title: | A Hybrid Integration and Parameter Estimation Algorithm Based on KTSMF for Sea-Surface Moving Targets Using Space-Based Bistatic Passive Radar. |
|---|---|
| Authors: | Xiang, Jianbing1,2 (AUTHOR), Huang, Lijia1,2 (AUTHOR), Zhong, Lihua1,2,3 (AUTHOR), Zhou, Guangyao1,2 (AUTHOR), Hu, Yuxin1,2,3 (AUTHOR) huyx@aircas.ac.cn |
| Source: | Remote Sensing. May2026, Vol. 18 Issue 10, p1479. 25p. |
| Subjects: | Parameter estimation, Bistatic radar, Signal processing, Pulse compression (Signal processing), Doppler effect, Signal-to-noise ratio |
| Abstract: | Highlights: What are the main findings? Proposes KTSMF to effectively mitigate severe range cell migration, Doppler frequency migration, Doppler ambiguity, and spectral aliasing effects under extremely low signal-to-noise ratio conditions. Combines intra-frame coherent integration and inter-frame incoherent integration to realize generalized and robust integration and estimation capability for space-based bistatic sea-surface targets with long-time observation. What are the implications of the main findings? Enables a generalized and robust capability under long-time observation and extremely low signal-to-noise ratio conditions for space-based bistatic sea-surface moving targets that are slow-moving, fast-moving, and highly maneuverable. Achieves a good balance between computational cost and detection performance. A space-based bistatic passive radar system, typically utilizing a satellite as the illuminator of opportunity and ground or aerial platforms as receivers, offers significant advantages for wide-area maritime surveillance, robust anti-jamming performance, and superior survivability. However, due to the limited transmit power and significant path loss over long-range propagation, the signal-to-noise ratio (SNR) of sea-surface targets is extremely low. To achieve effective detection and estimation, long-time integration is required, which can unfortunately induce severe range cell migration (RCM) and Doppler frequency migration (DFM) effects, resulting in integration gain loss and degraded detection performance. This article proposes a hybrid integration and parameter estimation algorithm based on the keystone transform and segmented matched filtering (KTSMF), which partitions the echoes into multiple frames and combines the keystone transform with segmented matched filters for integration. It not only effectively eliminates RCM and DFM effects in both intra-frame and inter-frame processing but also addresses Doppler ambiguity and Doppler aliasing effects, which enables a generalized processing capability for slow-moving, fast-moving, and highly maneuverable targets. Simulation results and analysis demonstrate that the proposed method achieves superior detection performance and parameter estimation accuracy compared to existing algorithms. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI 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 |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 194141004 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: A Hybrid Integration and Parameter Estimation Algorithm Based on KTSMF for Sea-Surface Moving Targets Using Space-Based Bistatic Passive Radar. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Xiang%2C+Jianbing%22">Xiang, Jianbing</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huang%2C+Lijia%22">Huang, Lijia</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhong%2C+Lihua%22">Zhong, Lihua</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhou%2C+Guangyao%22">Zhou, Guangyao</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hu%2C+Yuxin%22">Hu, Yuxin</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> huyx@aircas.ac.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. May2026, Vol. 18 Issue 10, p1479. 25p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Bistatic+radar%22">Bistatic radar</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Pulse+compression+%28Signal+processing%29%22">Pulse compression (Signal processing)</searchLink><br /><searchLink fieldCode="DE" term="%22Doppler+effect%22">Doppler effect</searchLink><br /><searchLink fieldCode="DE" term="%22Signal-to-noise+ratio%22">Signal-to-noise ratio</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? Proposes KTSMF to effectively mitigate severe range cell migration, Doppler frequency migration, Doppler ambiguity, and spectral aliasing effects under extremely low signal-to-noise ratio conditions. Combines intra-frame coherent integration and inter-frame incoherent integration to realize generalized and robust integration and estimation capability for space-based bistatic sea-surface targets with long-time observation. What are the implications of the main findings? Enables a generalized and robust capability under long-time observation and extremely low signal-to-noise ratio conditions for space-based bistatic sea-surface moving targets that are slow-moving, fast-moving, and highly maneuverable. Achieves a good balance between computational cost and detection performance. A space-based bistatic passive radar system, typically utilizing a satellite as the illuminator of opportunity and ground or aerial platforms as receivers, offers significant advantages for wide-area maritime surveillance, robust anti-jamming performance, and superior survivability. However, due to the limited transmit power and significant path loss over long-range propagation, the signal-to-noise ratio (SNR) of sea-surface targets is extremely low. To achieve effective detection and estimation, long-time integration is required, which can unfortunately induce severe range cell migration (RCM) and Doppler frequency migration (DFM) effects, resulting in integration gain loss and degraded detection performance. This article proposes a hybrid integration and parameter estimation algorithm based on the keystone transform and segmented matched filtering (KTSMF), which partitions the echoes into multiple frames and combines the keystone transform with segmented matched filters for integration. It not only effectively eliminates RCM and DFM effects in both intra-frame and inter-frame processing but also addresses Doppler ambiguity and Doppler aliasing effects, which enables a generalized processing capability for slow-moving, fast-moving, and highly maneuverable targets. Simulation results and analysis demonstrate that the proposed method achieves superior detection performance and parameter estimation accuracy compared to existing algorithms. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=194141004 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs18101479 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 25 StartPage: 1479 Subjects: – SubjectFull: Parameter estimation Type: general – SubjectFull: Bistatic radar Type: general – SubjectFull: Signal processing Type: general – SubjectFull: Pulse compression (Signal processing) Type: general – SubjectFull: Doppler effect Type: general – SubjectFull: Signal-to-noise ratio Type: general Titles: – TitleFull: A Hybrid Integration and Parameter Estimation Algorithm Based on KTSMF for Sea-Surface Moving Targets Using Space-Based Bistatic Passive Radar. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Xiang, Jianbing – PersonEntity: Name: NameFull: Huang, Lijia – PersonEntity: Name: NameFull: Zhong, Lihua – PersonEntity: Name: NameFull: Zhou, Guangyao – PersonEntity: Name: NameFull: Hu, Yuxin IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 10 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
