A Spaceborne Passive Localization Algorithm Based on MSD-HOUGH for Multiple Signal Sources
Recently, the passive synthetic aperture (PSA) technique has been used in passive localization to improve the position accuracy of single source by estimating the Doppler parameter of the received signal. However, in the presence of multiple sources, time-frequency aliasing will lead to serious cros...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/16/22/4303 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850147205024841728 |
|---|---|
| author | Liting Zhang Hao Huan Tao Ran Shangyu Zhang Yushu Zhang Hao Ding |
| author_facet | Liting Zhang Hao Huan Tao Ran Shangyu Zhang Yushu Zhang Hao Ding |
| author_sort | Liting Zhang |
| collection | DOAJ |
| description | Recently, the passive synthetic aperture (PSA) technique has been used in passive localization to improve the position accuracy of single source by estimating the Doppler parameter of the received signal. However, in the presence of multiple sources, time-frequency aliasing will lead to serious cross-term interference during Doppler signal extraction, resulting in low localization performance. To solve this problem, a spaceborne passive synthetic aperture localization algorithm based on the multiple-stay detector HOUGH transform (MSD-HOUGH) is proposed in this paper. Firstly, an improved convolutional neural network based on the adaptive histogram equalization method (AHE-CNN) is proposed to achieve source number estimation. Then, the PSA Doppler equations are established in the HOUGH domain, which can suppress the cross-term interference of the multiple emitters. Meanwhile, a multiple-stay detector (MSD) is designed to reduce the pseudo-peaks in HOUGH domain. The estimated source number determines when the MSD will be terminated. Finally, a PSA cost function is established based on the estimated Doppler parameter to achieve signal source localization. Experimental results show that compared with other localization methods, the proposed algorithm has a significant improvement for multiple signal source localization. |
| format | Article |
| id | doaj-art-db6f2a706d58427b8048bd18e24efaf7 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-db6f2a706d58427b8048bd18e24efaf72025-08-20T02:27:38ZengMDPI AGRemote Sensing2072-42922024-11-011622430310.3390/rs16224303A Spaceborne Passive Localization Algorithm Based on MSD-HOUGH for Multiple Signal SourcesLiting Zhang0Hao Huan1Tao Ran2Shangyu Zhang3Yushu Zhang4Hao Ding5Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaSchool of Information and Electronics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Information and Electronics, Beijing Institute of Technology, Beijing 100081, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaRecently, the passive synthetic aperture (PSA) technique has been used in passive localization to improve the position accuracy of single source by estimating the Doppler parameter of the received signal. However, in the presence of multiple sources, time-frequency aliasing will lead to serious cross-term interference during Doppler signal extraction, resulting in low localization performance. To solve this problem, a spaceborne passive synthetic aperture localization algorithm based on the multiple-stay detector HOUGH transform (MSD-HOUGH) is proposed in this paper. Firstly, an improved convolutional neural network based on the adaptive histogram equalization method (AHE-CNN) is proposed to achieve source number estimation. Then, the PSA Doppler equations are established in the HOUGH domain, which can suppress the cross-term interference of the multiple emitters. Meanwhile, a multiple-stay detector (MSD) is designed to reduce the pseudo-peaks in HOUGH domain. The estimated source number determines when the MSD will be terminated. Finally, a PSA cost function is established based on the estimated Doppler parameter to achieve signal source localization. Experimental results show that compared with other localization methods, the proposed algorithm has a significant improvement for multiple signal source localization.https://www.mdpi.com/2072-4292/16/22/4303passive localizationmultiple signal sourcesHOUGHpassive synthetic aperture |
| spellingShingle | Liting Zhang Hao Huan Tao Ran Shangyu Zhang Yushu Zhang Hao Ding A Spaceborne Passive Localization Algorithm Based on MSD-HOUGH for Multiple Signal Sources Remote Sensing passive localization multiple signal sources HOUGH passive synthetic aperture |
| title | A Spaceborne Passive Localization Algorithm Based on MSD-HOUGH for Multiple Signal Sources |
| title_full | A Spaceborne Passive Localization Algorithm Based on MSD-HOUGH for Multiple Signal Sources |
| title_fullStr | A Spaceborne Passive Localization Algorithm Based on MSD-HOUGH for Multiple Signal Sources |
| title_full_unstemmed | A Spaceborne Passive Localization Algorithm Based on MSD-HOUGH for Multiple Signal Sources |
| title_short | A Spaceborne Passive Localization Algorithm Based on MSD-HOUGH for Multiple Signal Sources |
| title_sort | spaceborne passive localization algorithm based on msd hough for multiple signal sources |
| topic | passive localization multiple signal sources HOUGH passive synthetic aperture |
| url | https://www.mdpi.com/2072-4292/16/22/4303 |
| work_keys_str_mv | AT litingzhang aspacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT haohuan aspacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT taoran aspacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT shangyuzhang aspacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT yushuzhang aspacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT haoding aspacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT litingzhang spacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT haohuan spacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT taoran spacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT shangyuzhang spacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT yushuzhang spacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources AT haoding spacebornepassivelocalizationalgorithmbasedonmsdhoughformultiplesignalsources |