首页> 外文期刊>International Journal of Distributed Sensor Networks >Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position errors
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Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position errors

机译:在存在同步时钟偏差和传感器位置误差的情况下,使用到达角和到达时间差的测量来约束总最小二乘定位

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摘要

Based on measurements of angle of arrival and time difference of arrival, a method is proposed to improve the accuracy of localization with imperfect sensors. A derivation of the Cramér–Rao lower bound and the root mean square error is presented aimed at demonstrating the significance of taking synchronization errors into consideration. Subsequently, a set of pseudo-linear equations are constructed, based on which the constrained total least squares optimization model has been formulated for target localization and the Newton iteration is applied to obtain the source position and clock bias simultaneously. The theoretical performance of the constrained total least squares localization algorithm subject to sensor position errors and synchronization clock bias is derived, and a framework for the performance analysis is developed. In addition, the first-order error analysis illustrates that the proposed method can achieve the Cramér–Rao lower bound under moderate Gaussian noises by a mathematic derivation. Finally, simulation results are presented that verify the validity of the theoretical derivation and superiority of the new algorithm.
机译:基于到达角和到达时间差的测量,提出了一种提高传感器不完善定位精度的方法。提出了Cramér-Rao下界和均方根误差的推导,旨在证明考虑同步误差的重要性。随后,构造了一组伪线性方程,在此基础上,制定了约束总最小二乘法优化模型用于目标定位,并应用牛顿迭代法同时获取源位置和时钟偏差。推导了受传感器位置误差和同步时钟偏差约束的约束最小二乘定位算法的理论性能,建立了性能分析框架。此外,一阶误差分析表明,该方法可以通过数学推导在中等高斯噪声下实现Cramér-Rao下界。最后,仿真结果验证了该理论推导的有效性和新算法的优越性。

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