目標三維電磁散射參數(shù)化模型反演方法研究
發(fā)布時間:2018-11-06 14:52
【摘要】:目標電磁散射建模是基于模型的雷達目標識別系統(tǒng)的核心內(nèi)容之一。目標三維電磁散射參數(shù)化模型,特別是基于典型散射結構的參數(shù)化模型,用一組簡潔的參數(shù)描述目標,能夠為識別系統(tǒng)提供物理意義明確的多層次目標特征。從電磁散射測量數(shù)據(jù)中反演目標參數(shù)化模型是一個具有挑戰(zhàn)性的任務。論文圍繞從多角度合成孔徑雷達數(shù)據(jù)中建立目標三維散射特性參數(shù)化模型的問題,研究了反演框架以及其中的多個關鍵問題。在闡述清楚目標三維電磁散射參數(shù)化模型反演的內(nèi)涵、研究內(nèi)容和面臨挑戰(zhàn)的基礎上,論文第二章提出了一種基于典型散射結構的目標參數(shù)化模型反演框架,反演參數(shù)的物理意義更加清晰。該框架由模型初始化和參數(shù)優(yōu)化兩部分組成,利用多角度合成孔徑雷達數(shù)據(jù)反演目標參數(shù)化模型,具有較強的靈活性,便于綜合運用多種技術途徑完成建模任務。針對模型初始化問題,論文重點研究了目標二維/三維散射中心特征提取方法。基于稀疏表示與壓縮感知理論,論文第三章提出了一種二維散射中心提取方法,論文第四章提出了雷達目標三維成像方法和三維散射中心提取方法。所提方法利用目標圖像的先驗信息和模型時域響應的特點降低稀疏重構的維度和數(shù)據(jù)量,在模型維度較高的情況下仍可保證較高的效率。論文第五章提出了基于位置聚類分析、散射中心參數(shù)匹配、壓縮感知等三種利用多個二維散射中心重構三維散射中心的方法,這些方法降低了對多角度數(shù)據(jù)的要求,適應處理寬基線多角度合成孔徑雷達數(shù)據(jù),重構結果與目標結構對應性較好。針對目標典型散射結構參數(shù)化模型的參數(shù)優(yōu)化問題,論文第六章分別從圖像域約束準則和多角度圖像分割兩個角度提出了優(yōu)化方法,擴大收斂范圍,提高了參數(shù)優(yōu)化穩(wěn)健性。基于上述反演框架和關鍵方法,論文第七章提出了典型散射結構和點散射模型相結合的復雜目標參數(shù)化建模方法,實現(xiàn)了目標三維電磁散射參數(shù)化模型反演原型系統(tǒng),利用目標的電磁計算數(shù)據(jù)反演了目標全方位角-大俯仰角的三維電磁散射參數(shù)化模型的反演,并分析了模型的精度。實驗結果驗證了所提框架和方法的可行性及有效性。
[Abstract]:Target electromagnetic scattering modeling is one of the core contents of radar target recognition system based on model. The three-dimensional electromagnetic scattering parameterized model of target, especially the parameterized model based on typical scattering structure, describes the target with a set of simple parameters, which can provide the multi-level target characteristics with clear physical meaning for the recognition system. It is a challenging task to retrieve the target parameterized model from the electromagnetic scattering measurement data. In this paper, a parameterized model of 3-D scattering characteristics from multi-angle synthetic aperture radar (SAR) data is established, and the inversion framework and several key problems are studied. On the basis of explaining the connotation, research content and challenge of 3D electromagnetic scattering parameterized model inversion of target, in the second chapter, a target parameterized model inversion framework based on typical scattering structure is proposed. The physical meaning of the inversion parameters is clearer. The framework consists of two parts: model initialization and parameter optimization. The multi-angle synthetic aperture radar data is used to retrieve the target parameterized model. It has strong flexibility and is convenient to complete the modeling task by comprehensive use of various technical approaches. Aiming at the problem of model initialization, this paper focuses on the feature extraction method of two-dimensional / three-dimensional scattering centers. Based on sparse representation and compressed sensing theory, a two-dimensional scattering center extraction method is proposed in the third chapter. In the fourth chapter, the radar target three-dimensional imaging method and three-dimensional scattering center extraction method are proposed. The proposed method can reduce the sparse reconstruction dimension and the amount of data by using the prior information of the target image and the time-domain response of the model. The proposed method can still ensure a higher efficiency when the model dimension is high. In the fifth chapter, three methods based on location clustering analysis, scattering center parameter matching and compression perception are proposed to reconstruct 3D scattering center using multiple two-dimensional scattering centers. These methods reduce the requirement of multi-angle data. It adapts to the wide baseline multi-angle synthetic aperture radar (SAR) data, and the reconstruction results correspond well with the target structure. Aiming at the parametric optimization problem of typical scattering structure, in chapter 6, the optimization method is proposed from two angles of image domain constraint criterion and multi-angle image segmentation, which expands the convergence range and improves the robustness of parameter optimization. Based on the above inversion framework and key methods, in chapter 7, a complex target parameterized modeling method combined with typical scattering structure and point scattering model is proposed, and a prototype system of 3D electromagnetic scattering parameterized model inversion is implemented. The inversion of the three-dimensional electromagnetic scattering parameterized model with omni-directional angle and large pitch angle is obtained by using the electromagnetic calculation data of the target, and the accuracy of the model is analyzed. The experimental results verify the feasibility and effectiveness of the proposed framework and method.
【學位授予單位】:國防科學技術大學
【學位級別】:博士
【學位授予年份】:2016
【分類號】:TN957.52
,
本文編號:2314605
[Abstract]:Target electromagnetic scattering modeling is one of the core contents of radar target recognition system based on model. The three-dimensional electromagnetic scattering parameterized model of target, especially the parameterized model based on typical scattering structure, describes the target with a set of simple parameters, which can provide the multi-level target characteristics with clear physical meaning for the recognition system. It is a challenging task to retrieve the target parameterized model from the electromagnetic scattering measurement data. In this paper, a parameterized model of 3-D scattering characteristics from multi-angle synthetic aperture radar (SAR) data is established, and the inversion framework and several key problems are studied. On the basis of explaining the connotation, research content and challenge of 3D electromagnetic scattering parameterized model inversion of target, in the second chapter, a target parameterized model inversion framework based on typical scattering structure is proposed. The physical meaning of the inversion parameters is clearer. The framework consists of two parts: model initialization and parameter optimization. The multi-angle synthetic aperture radar data is used to retrieve the target parameterized model. It has strong flexibility and is convenient to complete the modeling task by comprehensive use of various technical approaches. Aiming at the problem of model initialization, this paper focuses on the feature extraction method of two-dimensional / three-dimensional scattering centers. Based on sparse representation and compressed sensing theory, a two-dimensional scattering center extraction method is proposed in the third chapter. In the fourth chapter, the radar target three-dimensional imaging method and three-dimensional scattering center extraction method are proposed. The proposed method can reduce the sparse reconstruction dimension and the amount of data by using the prior information of the target image and the time-domain response of the model. The proposed method can still ensure a higher efficiency when the model dimension is high. In the fifth chapter, three methods based on location clustering analysis, scattering center parameter matching and compression perception are proposed to reconstruct 3D scattering center using multiple two-dimensional scattering centers. These methods reduce the requirement of multi-angle data. It adapts to the wide baseline multi-angle synthetic aperture radar (SAR) data, and the reconstruction results correspond well with the target structure. Aiming at the parametric optimization problem of typical scattering structure, in chapter 6, the optimization method is proposed from two angles of image domain constraint criterion and multi-angle image segmentation, which expands the convergence range and improves the robustness of parameter optimization. Based on the above inversion framework and key methods, in chapter 7, a complex target parameterized modeling method combined with typical scattering structure and point scattering model is proposed, and a prototype system of 3D electromagnetic scattering parameterized model inversion is implemented. The inversion of the three-dimensional electromagnetic scattering parameterized model with omni-directional angle and large pitch angle is obtained by using the electromagnetic calculation data of the target, and the accuracy of the model is analyzed. The experimental results verify the feasibility and effectiveness of the proposed framework and method.
【學位授予單位】:國防科學技術大學
【學位級別】:博士
【學位授予年份】:2016
【分類號】:TN957.52
,
本文編號:2314605
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