基于谱估计的方位时间序列匹配算法

Research on Bearing Time Series Matching Algorithm Based on Spectrum Estimation

利用水声匹配场的思想建立了纯方位TMA(Target Motion Analysis)的匹配处理模型,把纯方位TMA改建为谱估计问题,进一步引入信号处理领域的MUSIC谱和快速傅里叶变换处理估计目标运动参数。数值仿真结果表明:子空间MUSIC算法较不稳定,搜索步长较大使得结果在真值附近波动较大,不能准确而稳定地收敛到真值;在采用大步长的情况下,快速傅里叶变换方法能得到更准确的结果。

In this paper,using the thought of acoustical match field to establish BTMA model,and the BTMA converted into spectral estimation problem is further introduced MUSIC spectrum signal processing and fast Fourier transform processing target motion parameter estimation.Numerical simulation results show that the subspace MUSIC algorithm is not stable.When the search step size is larger,the result will fluctuate greatly near the true value,and it can not converge to the true value accurately and stably,the fast Fourier transform method can get more accurate results.