Closed-Form Solution for Scaling a Wireless Acoustic Sensor Network

TL;DR

This paper introduces a closed-form solution for efficiently calibrating and synchronizing individual sensor nodes in a wireless acoustic sensor network without requiring built-in emitters, enabling scalable and flexible network expansion.

Contribution

It presents a novel method converting nonlinear TDOA equations into linear ones, allowing for simple, accurate calibration of new sensors in a WASN without full network recalibration.

Findings

High localization accuracy close to CRLB in simulations

Flexible calibration using known or arbitrary sources

Efficient linear solution for sensor calibration

Abstract

This study presents a closed-form solution for localizing and synchronizing an acoustic sensor node with respect to a Wireless Acoustic Sensor Network (WASN). The aim is to allow efficient scaling of a WASN by individually calibrating newly joined sensor nodes instead of recalibrating the entire array. A key contribution is that the sensor to be calibrated does not need to include a built-in emitter. The proposed method uses signals emitted from spatially distributed sources to compute time difference of arrival (TDOA) measurements between the existing WASN and a new sensor. The problem is then modeled as a set of multivariate nonlinear TDOA equations. Through a simple transformation, the nonlinear TDOA equations are converted into a system of linear equations. Then, weighted least squares (WLS) is applied to find an accurate estimate of the calibration parameters. Signal sources can either be known emitters within the existing WASN or arbitrary sources in the environment, thus allowing for flexible applicability in both active and passive calibration scenarios. Simulation results under various conditions show high joint localization and synchronization performance, often comparable to the Cram\'er-Rao lower bound (CRLB).