基于全相位预处理的时域多重信号分类波达方向估计方法

低信噪比下,针对宽带短脉冲情况下频域多重信号分类(MUSIC)中噪声子空间估计不稳定问题,提出一种基于全相位预处理的时域多重信号分类波达方向(DOA)估计方法。①对线列阵接收数据进行分组处理;②按搜索角度对各组数据进行相移预处理,并对各组数据预处理结果进行相加,得到一组新数据;③对线列阵接收数据在时域构建相移后的协方差矩阵,在更短数据长度下,稳定实现噪声子空间估计,并依据估计出的噪声子空间含有的正交特性,通过单位矩阵加法器得到相应空间谱估计值,实现波达方向估计。数值仿真和实测数据处理结果表明,相比频域MUSIC方法,该方法有效提高了线列阵接收数据协方差矩阵中信号含有量和信噪比,能够在更短数据长度情况下实现对噪声子空间的稳定估计,具有较好的稳定性和检测性能,提高了MUSIC方法在实际波达方向估计中的鲁棒性。

The time-domain multiple signal classification DOA estimation method based on app-phase preprocessing

For the instability problem of noise subspace estimated result of frequency domain multiple signal classification(MUSIC) under low signal-to-noise ratio, a time-domain multiple signal classification DOA estimation method based on all phase preprocessing was proposed. ①the linear array receiving data was grouped;②the data of each group was preprocessed by phase shift according to the search angle, and the preprocessing results of each group of data were added to get a new set of data;③the phase-shifted covariance matrix was constructed in the time domain, the noise subspace was stably estimated under the shorter data, the corresponding spatial spectrum estimation was obtained by the unit matrix adder according to the orthogonal characteristics of noise subspace, and the direction of arrival estimation value was obtained.The results of numerical simulation and measured data processing show that, compared with the frequency domain MUSIC method, this method effectively improves the signal content and signal-to-noise ratio of the covariance matrix, and realizes the stable estimation of the noise subspace under the case of shorter data.It has better stability and detection performance, and improves the robustness of the MUSIC method.