利用隔离小生境混合蛙跳方法联合估计波达方向和多普勒频率

Joint estimation of DOAs and Doppler frequency using isolation niche shuffled frog leaping algorithm

为了高效准确地联合估计波达方向(DOA)和多普勒频率,提出了基于二维MUSIC谱和隔离小生境混合蛙跳算法的联合谱估计方法。首先,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。然后,利用MUSIC算法和广义可观测矩阵构造联合估计的二维谱函数,将参数估计问题转化为多峰函数优化问题。最后,引入混合蛙跳算法(SFLA)并利用隔离小生境技术对混合蛙跳算法进行改进,使其适应于二维MUSIC谱多个极值的优化搜索,降低搜索计算量,得到DOA和多普勒频率的估计值。实验结果表明:在考虑信噪比为0dB的两个独立信号源的情况下,利用本文方法估计得到的DOA和多普勒频率的均方根误差分别为0.23°和0.005 5rad。该方法具有控制参数少、计算量小、参数自动配对等特点。

To estimate the Direction-of-Arrival （DOA） and Doppler frequency accurately and efficiently, a joint spectrum estimation method based on isolation niche technique and Shuffled Frog Leaping gorithm （SFLA） was presented. Firstly, an extended observable matrix containing the information of DOAs and Doppler frequency was constructed by using state-space model. Then, the joint spectrum function was fitted using MUSIC algorithm and the extended observable matrix and the joint estimation were converted to multidimensional nonlinear function optimization. Finally, the isolation niche technique was applied to modification of the SFLA and the search of 2D MUSIC spectrum peak, so that to reduce the computation loads and obtain the estimated DOAs and Dopplers. Experimental results indicate that the Root Mean Square Errors （RMSEs） of DOAs and Dopplers estimated from the proposed method are 0. 23°and 0. 005 5 rad respectively when the signal source number is two and the SNR is 0 dB. The proposed method gets high resolution parameter estimation with less computation loads and control terms, and the parameters are paired automatically.