We present a computationally-efficient algorithm for time-of-arrival (ToA) estimation that is robust under multipath propagation and strong interference. Our algorithm leverages multiple receive antennas to combine adaptive spatial filtering with autodifferentiation in order to super-resolve the tap of the first-arriving path at low computational complexity and without requiring model-order estimation. We use simulations with ray-traced indoor propagation channels to demonstrate significant performance improvements over conventional correlation-based ToA estimation methods and subspace techniques such as JADE.

翻译：本文提出一种计算高效的到达时间估计算法，该算法在多径传播和强干扰环境下具有鲁棒性。我们的算法利用多接收天线，将自适应空间滤波与自动微分技术相结合，从而以较低的计算复杂度实现对首达路径抽头延迟的超分辨率估计，且无需进行模型阶数估计。通过基于射线追踪的室内传播信道仿真实验，我们证明该算法相较于传统的基于相关的到达时间估计方法以及JADE等子空间技术，在性能上取得了显著提升。