无线电工程

在复杂电磁环境下，信号分选对提取有价值信息和保障系统稳定运行至关重要。早期基于传统参数的时分多址(Time Division Multiple Access, TDMA)信号分选方法在发射机结构多样化时面临挑战，综合考虑多种发射机结构对TDMA信号分选的影响，优选出频率偏移、突发功率、均方根误差向量幅度(Root Mean Square Error Vector Magnitude, RMSEVM)值作为信号分选特征，为有效利用三维特征空间的分布特性，采用三维基于密度的聚类算法(Density-Based Spatial Clustering of Applications with Noise, DBSCAN)进行信号分选，在保证聚类密度的同时降低计算复杂度。仿真结果表明，与传统的二维特征相比，在5～15 dB时，能够正确分选的用户信号数量有了1～2个的提升。

In a complex electromagnetic environment, signal sorting is crucial for extracting valuable information and ensuring the stable operation of the system. Early Time Division Multiple Access(TDMA) signal sorting methods based on traditional parameters face challenges when the transmitter structures are diversified. By comprehensively considering the impacts of various transmitter structures on TDMA signal sorting, frequency offset, burst power, and Root Mean Square Error Vector Magnitude(RMSEVM) value are optimally selected as the signal sorting features. To effectively utilize the distribution characteristics of the three-dimensional feature space, a three-dimensional Density-Based Spatial Clustering of Applications with Noise(DBSCAN) clustering algorithm is adopted for signal sorting, which reduces the computational complexity while ensuring the clustering density. The simulation results show that compared with the conventional two-dimensional features, the number of correctly discriminated user signals demonstrates an increase of 1～2 when the signal to noise ratio is at 5～15 dB.