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为减少算法运算量,将多级维纳滤波器引入到空时级联频率—到达角估计中,提出一种快速级联估计算法。快速算法通过简单的乘累加运算得到噪声子空间,避免了对阵列协方差矩阵的特征分解,减少了算法运算量。仿真结果表明:在信噪比大于5d B时,原有算法和快速算法性能相当,频率估计标准差均降到1MHz以下,DOA估计标准差小于1°。
In order to reduce the computational complexity of the algorithm, a multistage Wiener filter is introduced into the space-time frequency-arrival angle estimation of space-time to propose a fast cascade estimation algorithm. The fast algorithm obtains the noise subspace through a simple multiply-accumulate operation, avoids the feature decomposition of the array covariance matrix and reduces the computational complexity of the algorithm. The simulation results show that the original algorithm and the fast algorithm have the same performance when the signal-to-noise ratio is more than 5d B, the standard deviation of the frequency estimation falls below 1MHz, and the standard deviation of the DOA estimation is less than 1 °.