基于人工蜂群算法的波达方向和多普勒频率联合估计

将人工蜂群算法应用于似然函数的优化,实现了阵列信号波达方向(DOA)和多普勒频率的联合估计。利用状态空间模型构造包含DOA和多普勒频率信息的广义可观测矩阵,并构造包含该广义可观测矩阵的似然函数,将参数估计问题转化为多维非线性函数优化问题。进而利用人工蜂群算法对似然函数的求解过程进行优化,得到DOA和多普勒频率的估计值。算法保留了最大似然估计的渐近无偏估计性能,降低了似然函数求解的计算量,且参数能够自动配对。

Joint direction-of-arrival and Doppler frequency estimation based on artificial bee colony algorithm

To achieve the joint estimation of Direction-of-Arrival(DOA) and Doppler frequency in array signal processing,the artificial bee colony theory and algorithm are applied to optimize the likelihood function.First,the extended observability matrix containing the angle-frequency parameters is established using state-space model.Then,the likelihood function containing the extended observability matrix is used to convert the problem from parameter estimation to nonlinear multidimensional function optimization.Finally,artificial bee colony algorithm is applied to optimize the process of finding the solutions of the maximum likelihood estimator in order to estimate the DOA and Doppler frequency.The proposed method reserves the asymptotic unbiased estimation of the maximum likelihood estimator and reduces the computational burden to calculate the solution of the likelihood function.Besides,the estimated parameters can be paired automatically.