【摘要】 运用特征子空间方法的关键在于信号或噪声子空间的估计。实际上有些信号的统计特性通常随时间变化 ,为得到参数的实时估计值 ,需要随时根据新的阵列接收数据对信号或噪声子空间进行更新。首先建立了用于信号到达主向 (DOA)估计的SVD -ESPRIT算法 ,然后利用受限摄动分析提出了一种子空间跟踪算法。将该跟踪算法与SVD -ESPRIT算法相结合 ,得到的自适应ESPRIT算法可用于对时变的信号DOA进行跟踪估计。仿真计算结果验证了该算法的有效性。更多还原

【Abstract】 The key problem of eigen subspace methods is the estimation of signal or noise subspace. In practical situations, there exist signals whose statistic characteristics always change over time. To obtain the real time estimates of signal parameters which are time varying, it is necessary to update the signal or noise subspace according to newly received array sampled output. In this paper, SVD-ESPRIT algorithm is first proposed to achieve the estimation of DOA of impinging signals, then a subspace tracking algorithm via perturbation analysis is presented.With combination of the above subspace tracking algorithm with SVD-ESPRIT algorithm, an adaptive ESPRIT algorithm is presented to track the time varying DOAs. Computer simulation results are provided to demonstrate the effectiveness of the proposed algorithm.\;更多还原