非均匀阵元噪声条件下的近场声源定位

针对常规定位方法在空间非均匀高斯噪声背景下近场声源定位性能下降的问题,基于平面阵建立了近场声源信号模型,推导了空间非均匀阵元噪声条件下求解声源方位和距离信息的最大似然定位方法,并使用连续空间蚁群优化算法,解决了该最大似然方法在多维参数空间搜索的高运算复杂度问题,通过仿真实验验证了该方法的可行性和有效性.仿真实验表明,该方法估计精度较高,在低信噪比下方位和距离均方误差都小于常规最大似然方法,并且在高信噪比条件下方位和距离的均方误差都逼近克拉美-罗界.

Localization of Near-Field Sources in the Presence of Non-uniform Sensor Noise

To solve the problem of the declined performance of conventional maximum likelihood method in locating multiple near-field sources in the context of non-uniform spatial noise,the near-field signal model based on planar sensor array was firstly constructed and then the maximum likelihood localization method was derived in details to obtain the values of the azimuth and distance of sound sources. Moreover,the ant colony optimization algorithm for continuous space( ACOCS) was employed to further reduce the high computational complexity incurred in the multi-dimensional search process of the deduced maximum likelihood localization method. Simulations were conducted to validate the feasibility and efficiency of the proposed method. Simulation results showed that the proposed method has a higher estimation accuracy than the conventional maximum likelihood method under the lower mean squared error of both azimuth estimation and distance estimation,and can approach their respective Cramer-Rao Bound( CRB) at high signalto-noise ratio( SNR).