基于加权极大似然近场宽带目标定位技术研究

Study on Source Localization of Wideband Signals in Near-Field Using Weighted Maximum-Likelihood Estimation

近场宽带目标定位是阵列信号处理中的一项关键技术,为了解决宽带信号不同频率信噪比的不一致的问题,在充分研究基于常规极大似然的近场宽带目标定位方法的基础上,提出了一种新的基于加权极大似然的近场宽带目标定位方法。新方法对不同频率点数据的定位估计结果按信噪比进行不同的加权,从而得到更为精确的目标位置的估计。仿真研究表明,和比较传统的极大似然方法相比较,新方法可以有效地提高近场宽带目标的定位性能,具有很好的工程实际应用前景。

Source localization of wideband signals in near-field is a key issue in array signal processing.In order to solve the problem that SNRs of different frequencies are non-uniform,we propose a more efficient algorithm called Weighted Maximum-likelihood source localization（WML）,which is derived from the conventional Maximum-likelihood source localization.This proposed algorithm evidently improves the estimates of source localization by weighting the estimates according to the corresponding SNRs.Simulation results demonstrate that the proposed algorithm outperforms the conventional Maximum-likelihood solution,and it also can be utilized in practical application.