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Abstract：
This paper presents a new technique for estimating the two-dimensional direction of departure (2D-DOD) and direction of arrival (2D-DOA) in bistatic uniform planar array Multiple-Input Multiple-Output (MIMO) radar systems. The method is based on the reduced-dimension (RD) MUSIC algorithm, aiming to achieve improved precision and computational efficiency. Primarily, this pioneering approach efficiently transforms the four-dimensional (4D) estimation problem into two-dimensional (2D) searches, thus reducing the computational complexity typically associated with conventional MUSIC algorithms. Then, exploits the spatial diversity of array response vectors to construct a 4D spatial spectrum function, which is crucial in resolving the complex angular parameters of multiple simultaneous targets. Finally, the objective is to simplify the spatial spectrum to a 2D search within a 4D measurement space to achieve an optimal balance between efficiency and accuracy. Simulation results validate the effectiveness of our proposed algorithm compared to several existing approaches, demonstrating its robustness in accurately estimating 2D-DOD and 2D-DOA across various scenarios. The proposed technique shows significant computational savings and high-resolution estimations and maintains high precision, setting a new benchmark for future explorations in the field.
摘要：
本文提出了一种在双基地均匀平面阵列多输入多输出（MIMO）雷达系统中估计二维偏离方向（2D-DOD）和到达方向（2D-DOA）的新技术。该方法基于降维(RD)MUSIC算法，旨在提高精度和计算效率。首先,这种开创性的方法有效地将四维（4D）估计问题转化为二维（2D）搜索，从而降低了通常与传统MUSIC算法相关的计算复杂度。然后，利用阵列响应向量的空间多样性来构造4D空间谱函数，这对于解决多个同时目标的复杂角度参数至关重要。最后,目的是将空间谱简化为4D测量空间内的2D搜索,以实现效率和准确度之间的最佳平衡。仿真结果验证了我们提出的算法与几种现有方法相比的有效性，证明了其在各种场景下准确估计2D-DOD和2D-DOA的鲁棒性。所提出的技术显示出显著的计算节省和高分辨率估计，并保持高精度，为该领域未来的探索树立了新的基准。
