CAJ | 학술논문

针对现有的很多波达方向估计算法涉及到数据协方差矩阵的估计及其特征分解，甚至是求逆，导致运算复杂度高的问题，提出了基于快速傅里叶变换的子孔径M USIC波达方向估计算法。首先将等距线阵的接收数据矢量均匀划分为4个子矢量，然后对各个子矢量分别求FFT。将FFT的结果相干积累，并找到最大峰值点。最后，利用子矢量FFT 的结果中与最大峰值点对应的数据构造新的降维矢量，借助M USIC算法进行波达方向估计。该方法避免了直接接收数据的协方差矩阵估计和特征分解，有效地降低了运算量和计算复杂度，在阵元数和快拍数都较多的情况下优越性尤为明显。计算机仿真验证了所提方法的有效性和优越性。
침대현유적흔다파체방향고계산법섭급도수거협방차구진적고계급기특정분해，심지시구역，도치운산복잡도고적문제，제출료기우쾌속부리협변환적자공경M USIC파체방향고계산법。수선장등거선진적접수수거시량균균화분위4개자시량，연후대각개자시량분별구FFT。장FFT적결과상간적루，병조도최대봉치점。최후，이용자시량FFT 적결과중여최대봉치점대응적수거구조신적강유시량，차조M USIC산법진행파체방향고계。해방법피면료직접접수수거적협방차구진고계화특정분해，유효지강저료운산량화계산복잡도，재진원수화쾌박수도교다적정황하우월성우위명현。계산궤방진험증료소제방법적유효성화우월성。
The most available direction of arrival (DOA) estimation algorithms require covariance matrix estimation and eigendecomposition ,or even its inversion ,thus increasing the computational complexity . Here a novel sub‐aperture multiple sigal classification (M USIC) algorithm for DOA estimation based on fast Fourier transform (FFT ) is proposed . Firstly , each received data vector of uniform linear array (ULA) is portioned into four sub‐vectors .Then FFT is applied to each sub‐vector to achieve the coherent integration .By utilizing the data corresponding to the peaks of coherent integration in each sub‐vector ,a reduced‐dimensional data vector is constructed for DOA estimation in terms of M USIC .Since the full‐di‐mensional covariance matrix estimation and eigendecomposition are avoided ,the computational complexi‐ty is relatively low .Numerical examples are provided to verify the effectiveness and superiority of the proposed method .