【摘要】 针对非等间距线阵测向中的测向精度和相位模糊之间的矛盾,该文提出了一种基于四阶累积量的波达角(DOA)估计算法。该算法利用基线间的参差关系解相位模糊,以突破VESPA算法中参考阵元间距不大于半波长的限制,从而有效地提高了测向精度。依靠导向矢量、累积量矩阵特征值以及其对应的特征向量三者之间的关系,该算法实现了各基线的相位差与信号源的配对。仿真实验验证了该算法的有效性。更多还原

【Abstract】 A fourth-order cumulant-based DOA estimation method is presented,considering contradictions between direction finding precision and phase ambiguity in using non-uniform linear array to estimate the Direction Of Arrival(DOA).The new algorithm uses baseline ratio to solve ambiguity,and the constrain that the length of the displacement vectors joining the reference sensors must be less than half-wavelength of the signal is not need,thus accuracy of direction finding is effectively improved.According to the tripartite relationship among steering vector,the eigenvalues of the cumulant matrices and the eigenvectors corresponding to the eigenvalues,the phase differences of each baselines and the signals are automatically paired in the algorithm.The performance of the algorithm is effectively demonstrated with simulation.更多还原