Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors
This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2013-04-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/13/4/5381 |
| _version_ | 1811303771383267328 |
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| author | Elena Rufo José L. Lázaro Alfredo Gardel Raúl Fernández-Recio Ignacio Bravo Patricia López-Rodríguez |
| author_facet | Elena Rufo José L. Lázaro Alfredo Gardel Raúl Fernández-Recio Ignacio Bravo Patricia López-Rodríguez |
| author_sort | Elena Rufo |
| collection | DOAJ |
| description | This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation. |
| first_indexed | 2024-04-13T07:53:58Z |
| format | Article |
| id | doaj.art-beee0fdb59a84eea8bb55643ce571c0b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T07:53:58Z |
| publishDate | 2013-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-beee0fdb59a84eea8bb55643ce571c0b2022-12-22T02:55:28ZengMDPI AGSensors1424-82202013-04-011345381540210.3390/s130405381Computational Burden Resulting from Image Recognition of High Resolution Radar SensorsElena RufoJosé L. LázaroAlfredo GardelRaúl Fernández-RecioIgnacio BravoPatricia López-RodríguezThis paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation.http://www.mdpi.com/1424-8220/13/4/5381high resolution radarradar imageryISARtarget recognitioncomputational burdenNCC |
| spellingShingle | Elena Rufo José L. Lázaro Alfredo Gardel Raúl Fernández-Recio Ignacio Bravo Patricia López-Rodríguez Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors Sensors high resolution radar radar imagery ISAR target recognition computational burden NCC |
| title | Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors |
| title_full | Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors |
| title_fullStr | Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors |
| title_full_unstemmed | Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors |
| title_short | Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors |
| title_sort | computational burden resulting from image recognition of high resolution radar sensors |
| topic | high resolution radar radar imagery ISAR target recognition computational burden NCC |
| url | http://www.mdpi.com/1424-8220/13/4/5381 |
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