论文标题
通过最大correntropy标准缓解NLOS的神经动力学TDOA定位
Neurodynamic TDOA localization with NLOS mitigation via maximum correntropy criterion
论文作者
论文摘要
在本文中，我们利用了最大的CorrentRopy Criterion（MCC）来稳健地在存在非线观察（NLOS）传播条件下稳健的传统时间差异（TDOA）位置估计器。为了提高统计效率，基于Correntropy的稳健损失是通过对源位置和发作时间的联合估计而不是在传感器收集时间戳后生成的TDOA对应物来施加的，而不是TDOA对应物。然后，我们采用一种神经动力学优化方法来应对高度非凸MCC公式。此外，我们研究了相应的投影型神经网络模型的平衡局部稳定性。代表性NLOS传播方案中的仿真研究表明，我们的神经动力学强大的TDOA定位解决方案能够在定位准确性方面超过几种现有方案。
In this paper, we exploit the maximum correntropy criterion (MCC) to robustify the traditional time-difference-of-arrival (TDOA) location estimator in the presence of non-line-of-sight (NLOS) propagation conditions. For the sake of statistical efficiency, the correntropy-based robust loss is imposed on the underlying time-of-arrival composition via joint estimation of the source position and onset time, instead of the TDOA counterpart generated in the postprocessing of sensor-collected timestamps. We then employ a neurodynamic optimization approach to tackle the highly nonconvex MCC formulation. Furthermore, we examine the local stability of equilibrium for the corresponding projection-type neural network model. Simulation investigations in representative NLOS propagation scenarios demonstrate that our neurodynamic robust TDOA localization solution is capable of outperforming several existing schemes in terms of positioning accuracy.
