| 引用本文: | 王嘉恒，阮 铭，谢菊兰，李会勇，何子述. 阵列宽发模式下基于极大极小算法的二维DOA估计方法[J]. 雷达科学与技术, 2026, 24(3): 280-288.[点击复制] |
| WANG Jiaheng, RUAN Ming, XIE Julan, LI Huiyong, HE Zishu. Two-Dimensional DOA Estimation Method Based on Majorization-Minimization Algorithm Under Array Wide Transmission Mode[J]. Radar Science and Technology, 2026, 24(3): 280-288.[点击复制] |
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| 摘要: |
| 为解决阵列宽发模式下二维波达方向（DOA）估计面临的信号相干性强、信噪比低及计算复杂等问题，本文提出一种基于极大极小（MM）算法的二维 DOA 估计方法。该方法基于均匀矩形平面阵列信号模型，在奇异值分解（SVD）降维的基础上，通过接收数据的等价变形实现二维角度解耦，将二维DOA估计问题转化为两个一维问题。基于压缩感知理论构建了优化模型，在 MM 算法框架下通过交替迭代的方法完成了优化问题求解。仿真实验表明，所提方法的DOA估计均方根误差（RMSE）优于对比算法，具备解相干能力，能够实现高精度DOA估计，可提升低截获概率（LPI）雷达的参数估计能力。 |
| 关键词: 低截获雷达 波达方向估计 压缩感知 极大极小算法 |
| DOI：DOI:10.3969/j.issn.1672-2337.2026.03.005 |
| 分类号:TN957.51 |
| 基金项目:国家自然科学基金（62231006）； 四川省科技厅科技计划（2023ZHJY0011） |
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| Two-Dimensional DOA Estimation Method Based on Majorization-Minimization Algorithm Under Array Wide Transmission Mode |
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WANG Jiaheng, RUAN Ming, XIE Julan, LI Huiyong, HE Zishu
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School of Information and Communication Engineering, University of Electronic Science and Technology of China,
Chengdu 611731，China
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| Abstract: |
| To address the challenges of strong signal coherence, low signal-to-noise ratio, and complex calculation in two-dimensional direction of arrival （DOA） estimation under wide beam transmission mode, this paper proposes a two-dimensional DOA estimation method based on the majorization-minimization （MM） algorithm. The method is based on a uniform rectangular planar array signal model. On the basis of singular value decomposition （SVD） for dimensionality reduction, the two-dimensional angle decoupling is achieved through the equivalent transformation of the received data, and the two-dimensional DOA estimation problem is transformed into two one-dimensional problems. An optimization model is constructed based on compressed sensing theory, and the optimization problem is solved by an alternating iterative method within the MM algorithm framework. Simulation results demonstrate that the root mean square error （RMSE） of DOA estimation in the proposed method is lower than that of the comparative algorithms, and it has the capability of decoherence. It enables high-precision DOA estimation, thereby improving the parameter estimation capability of low probability of intercept （LPI） radars. |
| Key words: low probability of intercept（LPI） radar direction of arrival（DOA） estimation compressed sensing majorization-minimization algorithm |
