2014
DOI: 10.1049/sbra504e
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Inverse Synthetic Aperture Radar Imaging: Principles, Algorithms and Applications

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Cited by 248 publications
(167 citation statements)
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“…The second exponentials of if-1 (̂, ) and if-2 (̂, ) in (9) account for Doppler and the third exponentials are the residual video phase (RVP). The RVP of each channel can be removed by the translation motion compensation (TMC) algorithms [7]. Taking FT of in (9) in terms of , the two temporary HRRPs of the double channels in the frequency domain, after the two RVPs and constant terms are removed, are obtained as follows:…”
Section: Pulse Compression Via Dual-channel Dechirpingmentioning
confidence: 99%
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“…The second exponentials of if-1 (̂, ) and if-2 (̂, ) in (9) account for Doppler and the third exponentials are the residual video phase (RVP). The RVP of each channel can be removed by the translation motion compensation (TMC) algorithms [7]. Taking FT of in (9) in terms of , the two temporary HRRPs of the double channels in the frequency domain, after the two RVPs and constant terms are removed, are obtained as follows:…”
Section: Pulse Compression Via Dual-channel Dechirpingmentioning
confidence: 99%
“…Inverse synthetic aperture radar (ISAR) is a powerful tool in many civilian and military fields such as air traffic control, harbor and river traffic surveillance, and remote sensing of satellites, benefiting from the superiorities such as robust performance under all-weather conditions, high-resolution images, and long detection range [1][2][3][4][5][6][7][8]. The high-resolution image even can be utilized for the purposes of feature extraction and target recognition of noncooperative targets [9][10][11].…”
Section: Introductionmentioning
confidence: 99%
“…바이스태틱 레이다 시스템의 개념을 확장하여 송/수신 기능을 모두 수행하는 여러 대의 레이다들을 분리시켜 분포시킴으로써, statistic 다중입력-다중출력(Multiple-Input Multiple-Output: MIMO) 레이다 네트워크(network) 시스템 을 정의할 수 있다 [1] . 여기서 MIMO 레이다 시스템을 통 해 표적을 관측할 경우, 여러 관측각도에서의 바이스태틱 ISAR 영상들을 형성할 수 있다.…”
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“…여기서 MIMO 레이다 시스템을 통 해 표적을 관측할 경우, 여러 관측각도에서의 바이스태틱 ISAR 영상들을 형성할 수 있다. 만약 상기 형성된 모든 바이스태틱 ISAR 영상들을 인코히리언트(incoherent)하게 합성할 수 있다면, 표적에 대한 다중각도에서의 바이스태 틱 산란분포를 하나의 2차원 영상의 형태로 도시하는 MIMO ISAR 영상을 형성할 수 있다 [1] . 상기 MIMO ISAR 영상은 표적 식별 수행 시 높은 정보량을 지닌 유용한 특 징 벡터(feature vector)로 활용될 수 있을 뿐만 아니라, 표 적에 대한 산란 매커니즘 분석 시 유용한 지표로써 활용 될 수 있다.…”
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