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Source Localization in Acoustic Sensor Networks via Constrained Least-Squares Optimization Using AOA and GROA Measurements

机译:使用AOA和GROA测量,通过约束最小二乘优化的声学传感器网络中的源定位

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摘要

A constrained least-squares (CLS) 3D source localization method is presented for acoustic sensor networks with sensor position errors. The proposed approach uses angles of arrivals (AOAs) and gain ratios of arrival (GROAs) measured simultaneously at each node to estimate the source position jointly. Compared to AOA-only localization methods, the GROAs can be used in conjunction with AOA measurements so as to get more accurate results by exploiting the geometrical relationship between these two measurements. Compared to time difference of arrival localization methods, the proposed algorithm does not require accurate time synchronization over different nodes. The theoretical mean-square error matrices of the proposed approach are derived and they are exactly equal to the Cramér–Rao bound for Gaussian noise under the small error condition. Simulations validate the performance of the proposed estimator.
机译:为具有传感器位置误差的声学传感器网络呈现约束最小二乘(CLS)3D源定位方法。所提出的方法使用抵达(AOA)的角度,并在每个节点处同时测量到达的抵达比(檐陀)以共同估计源位置。与仅AOA的定位方法相比,檐陀可以与AOA测量结合使用,以便通过利用这两个测量之间的几何关系来获得更准确的结果。与到达定位方法的时间差相比,所提出的算法不需要在不同节点上准确时间同步。推导出所提出的方法的理论均方误差矩阵,它们与小错误条件下的高斯噪声的克拉姆·饶乐队完全相同。仿真验证了所提出的估算者的表现。

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