Wu Haowei, Shi Yiqiao, Ou Jinglan
School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
Chongqing Key Laboratory of Space Information Network and Intelligent Information Fusion, Chongqing 400044, China.
Sensors (Basel). 2022 Jun 30;22(13):4949. doi: 10.3390/s22134949.
Three-dimensional (3-D) localization information, including elevation angle, azimuth angle, and range, is important for locating a single source with spherical wave-fronts. Aiming to reduce the high computational complexity of the classical 3-D multiple signal classification (3D-MUSIC) localization method, a novel low-complexity reduced-dimension MUSIC (RD-MUSIC) algorithm based on the sparse symmetric cross array (SSCA) is proposed in this article. The RD-MUSIC converts the 3-D exhaustive search into three one-dimensional (1-D) searches, where two of them are obtained by a two-stage reduced-dimension method to find the angles, and the remaining one is utilized to obtain the range. In addition, a detailed complexity analysis is provided. Simulation results demonstrate that the performance of the proposed algorithm is extremely close to that of the existing rank-reduced MUSIC (RARE-MUSIC) and 3D-MUSIC algorithms, whereas the complexity of the proposed method is significantly lower than that of the others, which is a big advantage in practice.
三维（3-D）定位信息，包括仰角、方位角和距离，对于利用球面波前定位单个源非常重要。为了降低经典三维多重信号分类（3D-MUSIC）定位方法的高计算复杂度，本文提出了一种基于稀疏对称交叉阵列（SSCA）的新型低复杂度降维MUSIC（RD-MUSIC）算法。RD-MUSIC将三维穷举搜索转换为三个一维（1-D）搜索，其中两个通过两阶段降维方法来找到角度，另一个用于获得距离。此外，还提供了详细的复杂度分析。仿真结果表明，所提算法的性能与现有的降秩MUSIC（RARE-MUSIC）和3D-MUSIC算法极为接近，而所提方法的复杂度明显低于其他算法，这在实际应用中是一个很大的优势。
