Acoustic Source Localization for an Indoor Pass-By Measurement System; A Beamforming Approach Using a One-Dimensional Sparse Microphone Array

Abstract

Accurate source localization of acoustic sources is critical for vehicle noise analysis. This thesis examines the possibility of using sparse microphone arrays, which are part of an indoor pass-by measurement rig, as acoustic cameras in a near-field scenario. Four different techniques were implemented, validated and comparatively analysed. Three beamforming techniques, Delay and Sum (DS), Minimum Variance Distortionless Response (MVDR) and Functional Beamforming (FBF). The fourth technique is a post-processing algorithm, A Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS). Each technique was evaluated based on spatial resolution, robustness to noise, array element imperfections and performance on real measurement data. The DS beamformer demonstrated robustness to array element sensitivity variations and placement errors, but was limited under low Signal-to-Noise Ratio (SNR) conditions due to its broad mainlobe and elevated side-lobe levels. MVDR and FBF, both implemented using Cross Spectral Matrices (CSM), offered improved directional accuracy and noise suppression capabilities. FBF introduced a tunable order factor which enhances control of side-lobe suppression and mainlobe width, making it particularly useful as a pre-processing step for DAMAS. The DAMAS algorithm was implemented as a post-beamforming processing tool, offering improved spatial resolution, although its performance was based heavily on the quality of the beamformer input. Validation included both simulations and real measurements conducted inside a semi-anechoic pass-by test rig, using stationary vehicle signals. All techniques successfully localized tonal sources across a frequency range of 40 − 1600 Hz. However, the spatial resolution remained constrained by array aperture size and wavelength. Ground reflections introduced interference patterns that reduced accuracy at certain frequencies, mimicking the acoustic behaviour expected in a road-like environment. The thesis concludes that combining MVDR and FBF for initial localization and DAMAS for source separation provides a flexible approach for acoustic source localization. The importance of accurate propagation and time delay modelling, calibration and signal processing was highlighted as a key factor to achieving reliable beamforming results in vehicle acoustic pass-by measurements