Multireceiver SAS Imagery Based on Monostatic Conversion
To use monostatic based imaging algorithms for multireceiver synthetic aperture sonar, the monostatic conversion is often carried out based on phase centre approximation, which is widely exploited by multireceiver SAS systems. This article presents a novel aspect for dealing with the multireceiver S...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IEEE
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/359c9fa481cb49b88d2397db9622e9bc |
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| Sumario: | To use monostatic based imaging algorithms for multireceiver synthetic aperture sonar, the monostatic conversion is often carried out based on phase centre approximation, which is widely exploited by multireceiver SAS systems. This article presents a novel aspect for dealing with the multireceiver SAS imagery, which still depends on the idea of monostatic conversion. The approach in this article is based on Loffeld's bistatic formula that consists of two important terms, i.e., quasi monostatic and bistatic deformation terms. Our basic idea is to preprocess the bistatic deformation term and then incorporate the quasi monostatic term into an analogous monostatic spectrum. With this new spectrum, traditional imaging algorithms designed for monostatic synthetic aperture sonar can be easily exploited. In this article, we show that Loffeld's bistatic formula can be reduced to the same formula as spectrum based on phase centre approximation when certain conditions are met. Based on our error analysis, the maximum error magnitude of PCA method is about 1 rad, which would noticeably affect the SAS imagery. Fortunately, the error magnitude of presented method can be always kept within <inline-formula><tex-math notation="LaTeX">${{\rm{\pi }} \mathord{/ {\vphantom {{\rm{\pi }} 4}} \kern-\nulldelimiterspace} 4}$</tex-math></inline-formula>. It means that Loffeld's bistatic formula provides a more accurate approximation of the spectrum compared to that based on phase centre approximation. After that, this article develops a new imaging scheme and presents imaging results. Based on quantitative comparisons, the presented method well focuses multireceiver SAS data, and it provides better image compared to phase centre approximation method. |
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