基于稀疏孔徑的聯(lián)合稀疏約束干涉ISAR機(jī)動(dòng)目標(biāo)三維成像

張榆紅; 邢孟道; 徐剛

doi:10.11999/JEIT150125

基于稀疏孔徑的聯(lián)合稀疏約束干涉ISAR機(jī)動(dòng)目標(biāo)三維成像

doi: 10.11999/JEIT150125

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出版歷程
- 收稿日期: 2015-01-22
- 修回日期: 2015-04-14
- 刊出日期: 2015-09-19

Joint Sparsity Constraint Interferometric ISAR Imaging for 3-D Geometry of Maneuvering Targets with Sparse Apertures

摘要

摘要: InISAR系統(tǒng)能夠?qū)崿F(xiàn)對(duì)目標(biāo)的3維幾何估計(jì)，更加有利于目標(biāo)的分類和識(shí)別。同時(shí)多功能ISAR/InISAR系統(tǒng)針對(duì)的多是機(jī)動(dòng)性很強(qiáng)的目標(biāo)，在某些情況下對(duì)單個(gè)目標(biāo)僅能獲取稀疏孔徑觀測(cè)，尤其是在目標(biāo)存在機(jī)動(dòng)特性的情況下，更是增加了ISAR成像的難度，這些對(duì)傳統(tǒng)的ISAR成像算法提出了挑戰(zhàn)。為了解決上述這些問(wèn)題，該文針對(duì)機(jī)動(dòng)目標(biāo)提出一種基于稀疏孔徑的聯(lián)合稀疏約束InISAR 3維成像方法。對(duì)勻加速轉(zhuǎn)動(dòng)的目標(biāo)，回波的多普勒調(diào)制可以建模成線性調(diào)頻的形式，并用chirp-傅里葉字典來(lái)表征其機(jī)動(dòng)性。接著將聯(lián)合的多通道InISAR 2維成像轉(zhuǎn)化為聯(lián)合稀疏約束的最優(yōu)化求解問(wèn)題，并用改進(jìn)的OMP算法進(jìn)行求解。然后利用各個(gè)通道估計(jì)的ISAR圖像和調(diào)頻參數(shù)實(shí)現(xiàn)對(duì)目標(biāo)的3維幾何重構(gòu)。相比于單通道獨(dú)立成像，聯(lián)合多通道稀疏約束成像能獲得更好的2維和3維成像結(jié)果。最后，進(jìn)行實(shí)測(cè)數(shù)據(jù)實(shí)驗(yàn)以驗(yàn)證該文算法的有效性。
- 干涉逆合成孔徑雷達(dá) /
- 機(jī)動(dòng)目標(biāo) /
- 稀疏孔徑 /
- 聯(lián)合多通道成像 /
- 3D幾何模型
Abstract: Interferometric Inverse SAR (InISAR) is capable of acquiring three-dimensional image of the moving targets, which is much helpful to the target classification and identification. Meanwhile, multifunctional ISAR/InISAR system aims at maneuvering targets and only sparse aperture measurements are available for each target, which is a challenge to the conventional ISAR imaging algorithms. A joint sparsity-constraint InISAR 3-D imaging approaches is presented for maneuvering targets with sparse apertures. For a uniformly accelerated rotation target, the Doppler modulation in echo is formulated as chirp sensing code under a chirp-Fourier dictionary to represent the maneuverability. Then the joint multi-channel InISAR imaging approach is converted into a joint sparse constraint optimization. And a modified Orthogonal Matching Pursuit (OMP) algorithm is employed to solve the optimization. The 3-D target geometry is followed by using obtaining 2-D images and estimated chirp parameters. Finally, the experiment using measured data is performed to confirm the effectiveness of the proposed method.
- Interferometric Inverse SAR (InISAR) /
- Maneuvering targets /
- Sparse apertures /
- Joint multi-channel imaging /
- 3D geometry

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