RSL-Net: localising in satellite images from a radar on the ground
This letter is about localising a vehicle in an overhead image using FMCW radar mounted on a ground vehicle. FMCW radar offers extraordinary promise and efficacy for vehicle localisation. It is impervious to all weather types and lighting conditions. However the complexity of the interactions betwee...
| Asıl Yazarlar: | , , , |
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| Materyal Türü: | Journal article |
| Dil: | English |
| Baskı/Yayın Bilgisi: |
IEEE
2020
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| _version_ | 1826265587631783936 |
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| author | Tang, TY De Martini, D Barnes, D Newman, P |
| author_facet | Tang, TY De Martini, D Barnes, D Newman, P |
| author_sort | Tang, TY |
| collection | OXFORD |
| description | This letter is about localising a vehicle in an overhead image using FMCW radar mounted on a ground vehicle. FMCW radar offers extraordinary promise and efficacy for vehicle localisation. It is impervious to all weather types and lighting conditions. However the complexity of the interactions between millimetre radar wave and the physical environment makes it a challenging domain. Infrastructure-free large-scale radar-based localisation is in its infancy. Typically here a map is built and suitable techniques, compatible with the nature of sensor, are brought to bear. In this work we eschew the need for a radar-based map; instead we simply use an overhead image-a resource readily available everywhere. This letter introduces a method that not only naturally deals with the complexity of the signal type but does so in the context of cross modal processing. |
| first_indexed | 2024-03-06T20:26:01Z |
| format | Journal article |
| id | oxford-uuid:2f6b8cc6-bc57-45d1-a78f-57d4cfac9183 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T20:26:01Z |
| publishDate | 2020 |
| publisher | IEEE |
| record_format | dspace |
| spelling | oxford-uuid:2f6b8cc6-bc57-45d1-a78f-57d4cfac91832022-03-26T12:55:16ZRSL-Net: localising in satellite images from a radar on the groundJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:2f6b8cc6-bc57-45d1-a78f-57d4cfac9183EnglishSymplectic ElementsIEEE2020Tang, TYDe Martini, DBarnes, DNewman, PThis letter is about localising a vehicle in an overhead image using FMCW radar mounted on a ground vehicle. FMCW radar offers extraordinary promise and efficacy for vehicle localisation. It is impervious to all weather types and lighting conditions. However the complexity of the interactions between millimetre radar wave and the physical environment makes it a challenging domain. Infrastructure-free large-scale radar-based localisation is in its infancy. Typically here a map is built and suitable techniques, compatible with the nature of sensor, are brought to bear. In this work we eschew the need for a radar-based map; instead we simply use an overhead image-a resource readily available everywhere. This letter introduces a method that not only naturally deals with the complexity of the signal type but does so in the context of cross modal processing. |
| spellingShingle | Tang, TY De Martini, D Barnes, D Newman, P RSL-Net: localising in satellite images from a radar on the ground |
| title | RSL-Net: localising in satellite images from a radar on the ground |
| title_full | RSL-Net: localising in satellite images from a radar on the ground |
| title_fullStr | RSL-Net: localising in satellite images from a radar on the ground |
| title_full_unstemmed | RSL-Net: localising in satellite images from a radar on the ground |
| title_short | RSL-Net: localising in satellite images from a radar on the ground |
| title_sort | rsl net localising in satellite images from a radar on the ground |
| work_keys_str_mv | AT tangty rslnetlocalisinginsatelliteimagesfromaradarontheground AT demartinid rslnetlocalisinginsatelliteimagesfromaradarontheground AT barnesd rslnetlocalisinginsatelliteimagesfromaradarontheground AT newmanp rslnetlocalisinginsatelliteimagesfromaradarontheground |