星载智能天线空域抗干扰快速算法研究

发布时间：2018-03-13 06:53

本文选题：低轨通信卫星　切入点：智能天线　出处：《南京理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：低轨卫星通信具有信号传播延时小和路径损耗小的特点,可以方便地实现全球任意位置的移动通信,已经成为当前移动通信领域的研究热点。本文将围绕低轨星载卫星通信中的智能天线技术展开研究。首先,针对低轨卫星通信中的"远近效应"问题和通信过程中地面用户和干扰角度动态变化的情况,研究了快速波束赋形和空域零陷方向图抗干扰技术,提出一种干扰子空间正交投影的快速零陷波束赋形算法。该算法采用迭代傅里叶变换(Iterative Fourier Transform,IFT)技术实现权重向量与方向图之间的快速转换,不仅可以优化得到任意形状的方向图,满足低轨卫星"等通量"赋形的需求,而且算法运算速度快,在通信过程中,能够在保证方向图主瓣区高增益覆盖的同时实时调整零陷位置跟踪干扰源。随后,为了解决波束赋形方法需要提前估计干扰源位置的问题,开展了任意形状方向图主瓣保形的自适应波束形成算法研究,提出了对角加载结构的主瓣保形自适应波束形成算法。该算法基于线性约束最小方差(Linear Constraint Minimum Variance,LCMV)准则,通过构建主瓣子空间约束以及权重系数模二次约束,来实现方向图主瓣增益控制下的自适应波束形成。算法给出了主瓣子空间约束的构建方法,推导了对角加载和具有保形意义的模约束之间的关系,进而给出了广义旁瓣相消(Generalized Sidelobe Canceler,GSC)架构下的对角加载实现模型。所提出算法不仅能够同时实现宽波束的主瓣保形和自适应抗干扰,而且采用GSC降秩结构有效降低了算法实现的复杂度。最后,完成了所提出的算法在19阵元三角栅格阵列的智能天线演示系统中的实测验证,主要包括:设计了智能天线演示系统测试专用软件,用于在紧缩场微波暗室环境下智能天线三维方向图的自动测试和增益标定;完成了算法的DSP移植和算法性能的实测验证。实测结果验证了本文所出的快速零陷波束赋形算法和主瓣保形自适应抗干扰算法的正确性、有效性和实时性,为智能天线技术的星载应用提供了有效的解决方案。
[Abstract]:Leo satellite communication has the characteristics of low signal propagation delay and low path loss, so it is convenient to realize mobile communication anywhere in the world. This paper will focus on the smart antenna technology in Leo satellite communication. First of all, Aiming at the problem of "near-far effect" in Leo satellite communications and the dynamic changes of ground users and interference angles in the communication process, the anti-jamming techniques of fast beamforming and spatial zero trapping pattern are studied. A fast beamforming algorithm based on orthogonal projection of interference subspace is proposed, in which the iterative Fourier transform (iterative Fourier transform) technique is used to realize the fast transformation between the weight vector and the pattern, which can not only optimize the pattern of arbitrary shape. It meets the demand of "equal flux" shape of Leo satellite, and the algorithm is fast. In the process of communication, the interference source can be adjusted in real time while keeping high gain coverage in the main lobe area of the pattern map. In order to solve the problem that the position of interference source needs to be estimated in advance in beamforming method, adaptive beamforming algorithm is studied, which preserves the main lobe of arbitrary shape pattern. In this paper, an adaptive beamforming algorithm for diagonal loading structure is proposed, which is based on linear constraint minimum variance linear Constraint Minimum variation LCMV. by constructing the principal lobe subspace constraint and the quadratic constraint of the modulus of weight coefficient. The algorithm gives the method of constructing the principal lobe subspace constraints and deduces the relationship between diagonal loading and conformal modulus constraints. Furthermore, a diagonal loading implementation model based on generalized sidelobe canceling generalized Sidelobe Cancelerator (GSC) architecture is presented. The proposed algorithm can not only realize the main lobe shape conserving and adaptive anti-jamming of wide beam simultaneously. Moreover, the complexity of the algorithm is effectively reduced by using the GSC rank reduction structure. Finally, the proposed algorithm is verified in the smart antenna demonstration system with 19 array triangular grid arrays. The main contents are as follows: a special testing software for smart antenna demonstration system is designed, which is used for automatic testing and gain calibration of smart antenna 3D pattern in the environment of compact field microwave darkroom. The DSP transplant of the algorithm is completed and the performance of the algorithm is verified. The experimental results verify the correctness, validity and real-time performance of the fast beamforming algorithm and the main lobe shape preserving adaptive anti-jamming algorithm proposed in this paper. It provides an effective solution for the space-borne application of smart antenna technology.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN927.2;TN821.91

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