DoA Reliability for Distributed Acoustic Tracking

Modified Particle Filtering Algorithm for Single Acoustic Vector Sensor DOA Tracking

The conventional direction of arrival (DOA) estimation algorithm with static sources assumption usually estimates the source angles of two adjacent moments independently and the correlation of the moments is not considered. In this article, we focus on the DOA estimation of moving sources and a modified particle filtering (MPF) algorithm is proposed with state space model of single acoustic vec...

Robust adaptive subspace extraction for DOA tracking

This paper addresses the problem of extracting a time-varying signal subspace from noisy signal measurements for direction-of-arrival (DOA) estimation and tracking. A robust adaptive method for extracting the signal subspace is developed based on robust statistics. The method is more resistant to the presence of outliers than existing adaptive methods. Robust DOA estimation and tracking are ach...

Acoustic DoA Estimation by One Unsophisticated Sensor

We show how introducing known scattering can be used in direction of arrival estimation by a single sensor. We first present an analysis of the geometry of the underlying measurement space and show how it enables localizing white sources. Then, we extend the solution to more challenging non-white sources like speech by including a source model and considering convex relaxations with group spars...

A distributed particle filtering approach for multiple acoustic source tracking using an acoustic vector sensor network

Comparison of two DOA tracking implementations for SDMA

Utilizing adaptive antenna arrays at the base stations of next generation mobile communication systems has been proposed as a promising approach to meet future requirements, e.g. spatio-temporal filtering techniques benefit from the detailed knowledge of the directional channel parameters. Unfortunately, in parameter estimation the computation of the signal subspace often turns out to be the mo...