Kang SeYoung, Kim TaeHyun, Chung WonZoo
Division of Computer and Communications Engineering, Korea University, Seoul 02841, Korea.
Agency for Defense Development, Daejeon 34186, Korea.
Sensors (Basel). 2020 Feb 20;20(4):1159. doi: 10.3390/s20041159.
We present a target localization method using an approximated error covariance matrix based weighted least squares (WLS) solution, which integrates received signal strength (RSS) and angle of arrival (AOA) data for wireless sensor networks. We approximated linear WLS errors via second-order Taylor approximation, and further approximated the error covariance matrix using a least-squares solution and the variance in measurement noise over the sensor nodes. The algorithm does not require any prior knowledge of the true target position or noise variance. Simulations validated the superior performance of our new method.
我们提出了一种基于近似误差协方差矩阵的加权最小二乘（WLS）解的目标定位方法，该方法融合了无线传感器网络的接收信号强度（RSS）和到达角（AOA）数据。我们通过二阶泰勒近似来近似线性WLS误差，并使用最小二乘解和传感器节点上测量噪声的方差进一步近似误差协方差矩阵。该算法不需要任何关于真实目标位置或噪声方差的先验知识。仿真验证了我们新方法的优越性能。
