Angle-of-Arrival (AoA) Factorization in Multipath Channels

Abstract

This paper considers the problem of estimating K angle of arrivals (AoA) using an array of M > K microphones. We assume the source signal is human voice, hence unknown to the receiver. Moreover, the signal components that arrive over K spatial paths are strongly correlated since they are delayed copies of the same source signal. Past works have successfully extracted the AoA of the direct path, or have assumed specific types of signals/channels to derive the subsequent (multipath) AoAs. Our method builds on the core observation that signals from multiple AoAs embed predictable delay-structures in them, which can be factorized through iterative alignment and cancellation. Simulation results show median AoA errors of < 4° for the first 3 AoAs. Real-world measurements, from a circular microphone array similar to Amazon Echo, show modest degradations. We believe the ability to infer even K = 3 AoAs can be helpful to various sensing and localization applications.