基于MISC共阵插值的无人机导航波束形成方法

李昊; 周帅; 于虹; 徐定杰

李昊,周帅,于虹,徐定杰.基于MISC共阵插值的无人机导航波束形成方法[J].电测与仪表,2026,63(7):101-108.
LI Hao,ZHOU Shuai,YU Hong,XU Dingjie.Adaptive beam forming method for UAV navigation based on the MISC coarray interpolation[J].Electrical Measurement & Instrumentation,2026,63(7):101-108.

基于MISC共阵插值的无人机导航波束形成方法

Adaptive beam forming method for UAV navigation based on the MISC coarray interpolation

DOI：10.19753/ j.issn1001-1390.2026.07.010

中文关键词: 无人机导航 MISC 阵列共阵插值协方差矩阵导向向量

英文关键词:UAV navigation, MISC array, coarray interpolation, covariance matrix, steering vector

基金项目:国家自然科学基金 (61673128)

作者中文名	作者英文名	单位
李昊	LI Hao	云南电网有限公司电力科学研究院, 昆明 650217
周帅	ZHOU Shuai	云南电网有限公司电力科学研究院, 昆明 650217
于虹	YU Hong	云南电网有限公司电力科学研究院, 昆明 650217
徐定杰	XU Dingjie	哈尔滨工业大学仪器科学与工程学院, 哈尔滨 150000

摘要点击次数: 202

中文摘要:

针对均匀直线阵列存在干扰抑制自由度受限以及阵元之间互耦的问题, 提出一种基于最大阵元间距约束(maximum inter-element spacing constraint, MISC)共阵插值的无人机导航自适应波束形成方法,能够增加干扰抑制自由度的数量,并且减少天线阵元之间互耦的影响。向量化MISC阵列协方差矩阵,构建差分共阵。由于差分共阵含有孔洞,将差分共阵插值为虚拟均匀直线阵列。构造基于原子范数最小化的优化问题, 并转化成凸优化问题,通过求解该问题,能够恢复出插值虚拟均匀直线阵列(interpolated virtual uniform linear array, IVULA)的信号向量。IVULA信号协方差矩阵具有Toeplitz结构,利用子空间旋转不变的特性, 能够计算出所有信号的方向。利用协方差拟合方法,能够估计出所有信号的功率。重新构建MISC阵列的干扰加噪声协方差矩阵,预测目标信号的导向向量, 并确定无人机导航接收器的波束形成加权向量。仿真实验表明: 文中所提出的方法适用于MISC阵列,比当前方法输出更高的信干噪比,对模型误差具有较好的鲁棒性。

英文摘要:

To address the issues of limited degrees-of-freedom for interference suppression and inter-element mutual coupling in a uniform linear array, this paper proposes an adaptive beam forming method for unmanned aerial vehicle (UAV) navigation based on maximum inter-element spacing constraint (MISC) coarray interpolation. This method aims to increase the number of degrees-of-freedom for interference suppression and reduce the mutual coupling effects between antenna elements. The MISC array covariance matrix is vectorized, and a difference coarray is constructed. Due to the presence of holes in the difference coarray, it is interpolated to form a virtual uniform linear array. An optimization problem based on atomic norm minimization is formulated and transformed into a convex optimization problem. By solving this problem, the signal vector of the interpolated virtual uniform linear array (IVULA) can be recovered. The IVULA signal covariance matrix has a Toeplitz structure, and by exploiting the subspace rotation-invariant property, the directions of all signals can be computed. The covariance fitting method is employed to estimate the powers of all signals. The interference plus noise covariance matrix of the MISC array is reconstructed, the steering vector of the desired signal is predicted, determining the beam forming weight vector for the UAV navigation receiver. Simulation experiments demonstrate that the proposed method is suitable for MISC arrays, outputs higher signal-plus-interference-to-noise ratios than current methods, and exhibits good robustness to model errors.

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