School of Mechanotronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China.
Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada.
Sensors (Basel). 2019 Oct 7;19(19):4326. doi: 10.3390/s19194326.
Various microphone array geometries (e.g., linear, circular, square, cubic, spherical, etc.) have been used to improve the positioning accuracy of sound source localization. However, whether these array structures are optimal for various specific localization scenarios is still a subject of debate. This paper addresses a microphone array optimization method for sound source localization based on TDOA (time difference of arrival). The geometric structure of the microphone array is established in parametric form. A triangulation method with TDOA was used to build the spatial sound source location model, which consists of a group of nonlinear multivariate equations. Through reasonable transformation, the nonlinear multivariate equations can be converted to a group of linear equations that can be approximately solved by the weighted least square method. Then, an optimization model based on particle swarm optimization (PSO) algorithm was constructed to optimize the geometric parameters of the microphone array under different localization scenarios combined with the spatial sound source localization model. In the optimization model, a reasonable fitness evaluation function is established which can comprehensively consider the positioning accuracy and robustness of the microphone array. In order to verify the array optimization method, two specific localization scenarios and two array optimization strategies for each localization scenario were constructed. The optimal array structure parameters were obtained through numerical iteration simulation. The localization performance of the optimal array structures obtained by the method proposed in this paper was compared with the optimal structures proposed in the literature as well as with random array structures. The simulation results show that the optimized array structure gave better positioning accuracy and robustness under both specific localization scenarios. The optimization model proposed could solve the problem of array geometric structure design based on TDOA and could achieve the customization of microphone array structures under different specific localization scenarios.
各种麦克风阵列几何形状（例如线性、圆形、方形、立方、球形等）已被用于提高声源定位的准确性。然而，这些阵列结构是否对于各种特定的定位场景是最优的，仍然存在争议。本文提出了一种基于 TDOA（到达时间差）的声源定位麦克风阵列优化方法。麦克风阵列的几何结构以参数形式建立。使用具有 TDOA 的三角测量方法构建空间声源位置模型，该模型由一组非线性多元方程组成。通过合理的变换，可以将非线性多元方程转换为一组可以通过加权最小二乘法近似求解的线性方程。然后，基于粒子群优化（PSO）算法构建了一个优化模型，结合空间声源定位模型，在不同的定位场景下优化麦克风阵列的几何参数。在优化模型中，建立了一个合理的适应度评估函数，可以综合考虑麦克风阵列的定位精度和鲁棒性。为了验证阵列优化方法，针对两种特定的定位场景，为每种定位场景构建了两种阵列优化策略。通过数值迭代模拟获得了最优的阵列结构参数。将本文提出的方法得到的最优阵列结构的定位性能与文献中提出的最优结构以及随机阵列结构进行了比较。仿真结果表明，在两种特定的定位场景下，优化后的阵列结构具有更好的定位精度和鲁棒性。所提出的优化模型可以解决基于 TDOA 的阵列几何结构设计问题，并可以实现不同特定定位场景下的麦克风阵列结构定制。
