Data extrapolation for high resolution radar imaging

Gupta, I.J.; Beals, M.J.; Moghaddar, A.

doi:10.1109/8.362783

Cited by 55 publications

(35 citation statements)

References 5 publications

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“…For the limited data case, modern spectral estimation methods are widely used to obtain high resolved images [2]. For the missing data (gapped data case) CLEAN algorithm [3] and 1-D AR model based extrapolation algorithms [4] have been used to fill the gaps before the Fourier transform of the backscattered data. In AR model based approaches, each available data segment (row or column) is modeled by Yule-Walker method.…”

Section: Introductionmentioning

confidence: 99%

On the use of Least-Squares Lattice structures for missing data in ISAR imaging

Copuroglu

Gültekin

Erer

2009

2009 4th International Conference on Recent Advances in Space Technologies

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In this work, we consider the spectral estimation of the gapped data encountered in inverse synthetic aperture radar (ISAR) imaging. For the estimation of missing data, we propose the use of Least-Square Lattice (LSL) Filters. The proposed method consists of interpolating the rows of two-dimensional backscattered data, where each row corresponds to the backscattered target data from a specific aspect angle. IFFT processing yields the enhanced spectral estimate of interpolated data. To demonstrate the effectiveness of the proposed algorithm, numerical results based on simulated data are presented.

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Section: Introductionmentioning

confidence: 99%

On the use of Least-Squares Lattice structures for missing data in ISAR imaging

Copuroglu

Gültekin

Erer

2009

2009 4th International Conference on Recent Advances in Space Technologies

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“…, N} be the one-dimensional spectrum data. The forward prediction of x(n) based on the p-th order AR model can be defined by [13,14] …”

Section: The Principle Of Spectrum Extrapolationmentioning

confidence: 99%

Enhanced Three-Dimensional Imaging for Multi-Circular Synthetic Aperture Radar

Yu¹,

Lin²,

Bao³

et al. 2017

PIER M

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Abstract-In multi-circular synthetic aperture radar (MCSAR) mode, resolution and sidelobes are two important parameters to consider when representing imaging quality, as in other SAR imaging modes. In this paper, three-dimensional (3-D) resolution and cone-shaped sidelobes of MCSAR are analyzed for a point target in the scene center under the Nyquist sampling criterion. The results of the analysis show that resolution can be improved, and cone-shaped sidelobes can be suppressed by increasing the system bandwidth and the length of synthetic aperture in the elevation direction. But this will make the system of acquiring data more difficult. It turns out that some digital signal processing techniques can enhance 3-D imaging quality of MCSAR. In this paper, a simple method based on spectrum extrapolation and interferometric phase masking is proposed to improve 3-D resolution and suppress cone-shaped sidelobes of MCSAR. Experimental results regarding a tank model in a microwave anechoic chamber demonstrate that this method is effective.

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“…In order to compare the performance, the 2 GHz(2～4 GHz), 4 GHz(2～6 GHz), and 6 GHz(2～8 GHz) bandwidth were used. 기존에 있던 연구에서는 고해상도를 얻기 위해 dataextrapolation 방법을 이용하였으나 [4] , 본 논문에서는 …”

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“…기존에 있던 연구에서는 고해상도를 얻기 위해 dataextrapolation 방법을 이용하였으나 [4] , 할 수 있다 [5] . 또한, 이 두 가지 정보들은 시간-주파 수 영역 해석법(time-frequency analysis)을 이용하여 동시에 추출해 낼 수 있다 [6] .…”

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Performance Improvement of Radar Target Classification Using UWB Measured Signals

Lee¹,

Lee²,

Choi³

et al. 2011

The Journal of Korean Institute of Electromagnetic Engineering

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본 논문에서는 광대역 레이다 측정 신호를 이용하여 5기종의 스케일 모델에 대해 표적 구분 실험을 수행하였 다. 대역폭의 크기에 따른 표적 구분 성능을 비교하기 위해 2 GHz(2～4 GHz), 4 GHz(2～6 GHz), 그리고 6 GHz(2 ～8 GHz)의 대역폭을 이용하였고, 시간-주파수 영역 해석법인 STFT와 CWT를 이용하여 각 표적에 대한 특성 벡터를 추출하였다. 여기서 추출된 특성 벡터들은 multi-layerd perceptron(MLP) 신경망 구분기의 입력으로 사용 되어 표적 구분 성능을 비교한 결과, 사용하는 주파수 대역폭이 넓을수록 표적 구분 성능이 향상되는 것을 확인 할 수 있었다. AbstractIn this paper, we performed radar target classification for the five scale models using ultra-wideband measured signal. In order to compare the performance, the 2 GHz(2～4 GHz), 4 GHz(2～6 GHz), and 6 GHz(2～8 GHz) bandwidth were used. 기존에 있던 연구에서는 고해상도를 얻기 위해 dataextrapolation 방법을 이용하였으나 [4] , 본 논문에서는

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Data extrapolation for high resolution radar imaging

Cited by 55 publications

References 5 publications

On the use of Least-Squares Lattice structures for missing data in ISAR imaging

On the use of Least-Squares Lattice structures for missing data in ISAR imaging

Enhanced Three-Dimensional Imaging for Multi-Circular Synthetic Aperture Radar

Performance Improvement of Radar Target Classification Using UWB Measured Signals

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