共形阵的优化设计及故障诊断算法研究
发布时间：2019-03-15 18:36
【摘要】：共形阵列是新世纪阵列天线技术发展的一个重要方向,它的应用将对相控阵雷达、隐身战机、移动通信基站、卫星通信等领域产生深远的影响。然而,由于共形阵空间结构的复杂性,传统的阵列分析与综合技术不再适用于共形阵。本文以共形阵列为对象,围绕阵元的稀布优化、波束形成以及阵元的故障诊断三个方面分别展开研究。全文的主要工作归纳如下:1.考虑共形阵的阵元方向性不一致等特殊性,给出基于欧拉旋转矩阵的方向图计算方法,并分别在圆柱阵和圆柱阵下进行仿真验证。2.考虑阵元的有向性,以降低峰值旁瓣电平为目标,采用遗传算法对共形半球面阵的阵元位置进行优化。阵元的位置由投影在坐标平面的极坐标表示,将半球阵的稀布优化问题转化为圆口径面内的稀布优化问题。在优化过程中,将阵元的最小间隔、阵列孔径以及阵元数作为约束条件,以均匀同心圆环为模板构造遗传算法的初始种群,利用阵元坐标的径向余量以及每层圆环的相位余量,提高布阵的自由度。3.考虑期望信号的方向偏差造成导向矢量失配以及副瓣的抑制问题,提出一种基于pl范数稀疏约束的稳健波束形成算法,并应用于共形阵。该算法首先利用小半径的球形不确定集约束对失配的导向矢量进行迭代矫正,然后对旁瓣区域的波束施加稀疏约束,并作为惩罚函数项加入到最小方差无失真响应(Minimum Variance Distortionless Response,MVDR)的目标函数中,实现旁瓣电平的抑制。4.结合近场测量技术,提出了一种基于稀疏贝叶斯学习(Sparse Bayesian learning,SBL)的阵元故障诊断方法。该方法考虑了阵列的“差分”激励向量的稀疏性,采用SBL对该向量进行稀疏重构,从而寻找出故障阵元的位置。所提出的方法适用于任意阵列的故障诊断问题。在共形圆柱阵下,将本方法与矩阵法进行了仿真对比实验。实验结果表明,在小故障比下,所提出的方法具有更高的诊断精确度。
[Abstract]:Conformal array is an important development direction of array antenna technology in the new century, its application will have a far-reaching impact on phased array radar, stealth fighter, mobile communication base station, satellite communication and so on. However, due to the complexity of conformal array spatial structure, traditional array analysis and synthesis techniques are no longer suitable for conformal arrays. In this paper, the conformal array is taken as the object, and the rarefied optimization of the array element, beamforming and fault diagnosis of the array element are studied respectively. The main work of the paper is summarized as follows: 1. Considering the inconsistencies of element orientation of conformal matrix, the calculation method of direction pattern based on Euler rotation matrix is given, and the simulation results are carried out under cylindrical array and cylindrical array, respectively. 2. In order to reduce the peak sidelobe level, genetic algorithm is used to optimize the element position of conformal hemispherical array considering the directivity of the array element. The position of the element is expressed by the polar coordinates projected on the coordinate plane, and the rarefied optimization problem of the hemispherical array is transformed into the rarefied optimization problem in the radius surface of the circle. In the optimization process, the minimum interval of array elements, the aperture of array and the number of array elements are taken as constraint conditions, and the initial population of genetic algorithm is constructed with uniform concentric ring as template. The radial redundancy of element coordinates and the phase margin of each layer ring are used to construct the initial population of genetic algorithm. Increase the degree of freedom of array arrangement. 3. In this paper, a robust beamforming algorithm based on sparse constraints of pl norm is proposed and applied to conformal arrays, considering the guidance vector mismatch and sidelobe suppression caused by the direction deviation of the desired signal. In this algorithm, the mismatched guidance vector is corrected iteratively by using the spherical uncertainty set constraint with small radius, then the beam in the sidelobe region is sparsely constrained, and added to the minimum variance distortion-free response (Minimum Variance Distortionless Response, as a penalty function term. In the objective function of MVDR), the suppression of sidelobe level is realized. 4. Based on sparse Bayesian learning (Sparse Bayesian learning,SBL (sparse Bayesian Learning), an array element fault diagnosis method is proposed based on the near-field measurement technique. In this method, the sparsity of the "difference" excitation vector of the array is considered, and the sparse reconstruction of the vector is carried out by using SBL to find out the location of the fault element. The proposed method is suitable for fault diagnosis of arbitrary array. In the conformal cylindrical array, the method is compared with the matrix method. The experimental results show that the proposed method has higher diagnostic accuracy under the condition of small fault ratio.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN820;TP18
本文编号：2440880
[Abstract]:Conformal array is an important development direction of array antenna technology in the new century, its application will have a far-reaching impact on phased array radar, stealth fighter, mobile communication base station, satellite communication and so on. However, due to the complexity of conformal array spatial structure, traditional array analysis and synthesis techniques are no longer suitable for conformal arrays. In this paper, the conformal array is taken as the object, and the rarefied optimization of the array element, beamforming and fault diagnosis of the array element are studied respectively. The main work of the paper is summarized as follows: 1. Considering the inconsistencies of element orientation of conformal matrix, the calculation method of direction pattern based on Euler rotation matrix is given, and the simulation results are carried out under cylindrical array and cylindrical array, respectively. 2. In order to reduce the peak sidelobe level, genetic algorithm is used to optimize the element position of conformal hemispherical array considering the directivity of the array element. The position of the element is expressed by the polar coordinates projected on the coordinate plane, and the rarefied optimization problem of the hemispherical array is transformed into the rarefied optimization problem in the radius surface of the circle. In the optimization process, the minimum interval of array elements, the aperture of array and the number of array elements are taken as constraint conditions, and the initial population of genetic algorithm is constructed with uniform concentric ring as template. The radial redundancy of element coordinates and the phase margin of each layer ring are used to construct the initial population of genetic algorithm. Increase the degree of freedom of array arrangement. 3. In this paper, a robust beamforming algorithm based on sparse constraints of pl norm is proposed and applied to conformal arrays, considering the guidance vector mismatch and sidelobe suppression caused by the direction deviation of the desired signal. In this algorithm, the mismatched guidance vector is corrected iteratively by using the spherical uncertainty set constraint with small radius, then the beam in the sidelobe region is sparsely constrained, and added to the minimum variance distortion-free response (Minimum Variance Distortionless Response, as a penalty function term. In the objective function of MVDR), the suppression of sidelobe level is realized. 4. Based on sparse Bayesian learning (Sparse Bayesian learning,SBL (sparse Bayesian Learning), an array element fault diagnosis method is proposed based on the near-field measurement technique. In this method, the sparsity of the "difference" excitation vector of the array is considered, and the sparse reconstruction of the vector is carried out by using SBL to find out the location of the fault element. The proposed method is suitable for fault diagnosis of arbitrary array. In the conformal cylindrical array, the method is compared with the matrix method. The experimental results show that the proposed method has higher diagnostic accuracy under the condition of small fault ratio.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN820;TP18
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