稀疏條件下基于散射點(diǎn)估計(jì)的SAR切片超分辨重建
doi: 10.11999/JEIT140121 cstr: 32379.14.JEIT140121
基金項(xiàng)目:
國家自然科學(xué)基金(61102166)資助課題
Super-resolution Reconstruction of SAR Section Based on Scattering Center Estimation and Sparse Constraint
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摘要: 從合成孔徑雷達(dá)(SAR)成像模型出發(fā)，在稀疏條件下，該文結(jié)合散射中心理論，從低分辨率圖像中估計(jì)高分辨率圖像的散射點(diǎn)參數(shù)，用若干sinc函數(shù)對(duì)感興趣目標(biāo)區(qū)(ROI)進(jìn)行重建并抑制旁瓣，獲得超分辨ROI切片?；诜蔷€性最小二乘(NLS)估計(jì)給出了該超分辨重建問題的迭代求解算法，并以TerraSAR-X數(shù)據(jù)進(jìn)行仿真驗(yàn)證，仿真結(jié)果表明，該文所提方法相比雙立方插值和1范數(shù)正則化方法能夠獲得更高的空間分辨率與目標(biāo)雜波比(TCR)。后續(xù)分析表明，散射點(diǎn)參數(shù)的估計(jì)精度受到信噪比和sinc函數(shù)重建3 dB帶寬共同影響，重建3 dB帶寬越大對(duì)噪聲的魯棒性越強(qiáng)。
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關(guān)鍵詞:
- 合成孔徑雷達(dá) /
- 超分辨重建 /
- 稀疏表示 /
- 非線性最小二乘估計(jì) /
- 魯棒性
Abstract: From the SAR imaging model, combining the scattering center theory, this paper estimates scattering centers of high resolution image from the low resolution image under the conditions of sparse. The Region Of Interesting (ROI) can be reconstructed by several sinc functions and the super resolution section is obtained after side lobe suppression. Based on the Nonlinear Least Squares (NLS) estimation, an iterative algorithm is employed to solve the super resolution reconstruction problem and the simulations are based on TerraSAR-X measurement data. Simulation results show that the proposed method is able to get higher spatial resolution and Target to Clutter Ratio (TCR) values as compared with bicubic interpolation and 1 norm regularization method. The analysis results show that the accuracy of the algorithm is affected by both the Signal to Noise Ratio (SNR) and the rebuilding 3 dB bandwidth of sinc function, the higher 3 dB bandwidth tends to be more robust to noise. -
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