摘要
扩展传播算子(EPM)算法是首先对数据进行扩展,再利用传播算子(PM)方法进行测向的一种算法,该算法充分利用了非圆信号的特点,分辨力和估计精度优于未充分利用非圆信号信息的经典高分辨算法。但是在实际信号测向中,由于阵元位置误差的存在,算法的估计性能会受到一定的影响。因此提出一种基于内插阵列变换的扩展传播算子(VIA-EPM)算法,该算法利用真实阵列流型与虚拟阵列流型之间的变换矩阵,将真实协方差矩阵变换为虚拟协方差矩阵,再对虚拟协方差矩阵进行分块并得出扩展传播算子,进而得出算法的空间谱函数。仿真实验表明:在存在阵元位置误差的情况下,新算法通过对阵元位置校准数据进行内插阵列变换(VIA),取得与阵元位置校准的EPM算法相当的估计性能,保持了阵列扩展能力以及高估计精度,在低信噪比情况下,基于扩展协方差矩阵的VIA-EPM算法的分辨力以及估计精度均要优于基于扩展数据矩阵的VIA-EPM算法。
Extended propagator method （EPM） utilizes propagator method for signal direction finding by extending the data first. It has better performance in resolution and accuracy than that of classical high resolution algorithms that don＇t make full use of the noncircular information. But the arrav element position error has an influence on the performance of the algorithm in the real direction finding. An EPM algorithm based on virtual interpolated array （VIA-EPM） is proposed. By utilizing transformation matrix which is obtained through the real array manifold and virtual array manifold, the real covariance matrix can be converted to virtual covariance matrix, and the spatial spectrum function can be obtained after splitting the virtual covariance matrix. Simulation results show that if sensor position errors exist, the performance of the new algorithm is similar to the calibrated EPM algorithm by using virtual interpolated array （VIA） for the calibrated sensor position data, and this algorithm also keeps the performance in array extension and high accuracy. The estimation accuracy and resolution of VIA-EPM algorithm based on extended covariance matrix is better than VIA-EPM algorithm based on extended data matrix in the case of low SNR.
出处
《电光与控制》
北大核心
2013年第2期61-65,共5页
Electronics Optics & Control
基金
陕西省电子信息系统综合集成重点实验室基金项目(201102Y05)
空军工程大学研究生创新课题(20110301)
空军工程大学电讯工程学院科研创新基金项目(DYCX1040)
关键词
阵列信号处理
波达方向(DOA)估计算法
扩展传播算子算法
内插阵列变换
array signal processing
direction of arrival （DOA） estimation algorithm
extended propagatormethod
virtual interpolated array
