阵列天线通道不一致性校正的辅加阵元法

MUSIC算法是一种基于特征值分解的超分辨DOA估计算法,在理想阵列条件下,其估计性能良好,但当信号模型与实际信号环境不匹配,即存在系统误差时,MUSIC算法的估计性能会严重下降,甚至失效。针对模型中普遍存在的通道不一致性误差,本文首先分析了此类误差对测向性能的影响,并提出了一种通道误差校正的简易算法,该方法通过对来自辅加阵元信号的数据信息进行处理,获取通道不一致性误差的估计,通过误差补偿有效地抑制了通道不一致性的影响,提高了DOA估计的性能。给出了应用该方法的具体步骤,计算机仿真结果证明了该算法的有效性。

Calibration method for array antenna channel uncertainty using instrumental sensor

MUSIC algorithm is a hyper-resolution DOA estimation method which is based on eigenvalue decomposition,it has excellent estimation performance under ideal cases,but its performance degrades significantly and even can not work when the model dose not match with the reality,which means there are system errors.This paper analyzes the influence of array antenna channel uncertainty which is very common in model at first,and then puts forward an easy algorithm for channel uncertainty calibration,the method obtain the estimation of the channel uncertainty errors by processing the data information of the instrumental sensor's signal,the influence of channel uncertainty is restrained and the performance of DOA estimation is improved through errors compensation.The detailed step of the proposed method is given,and computer simulations are presented to illustrate the validity of the method.