Source parameter estimation of aero‐acoustic emitters using non‐linear least squares and conventional methods

This is the authors' abstract. We don't add key points for this paper.

Three passive acoustic data processing applications using a non‐linear least squares (NLS) approach are reviewed for parameter estimation of a variety of aero‐acoustic emitters and observables: (i) flight motion parameter estimation of a turboprop aircraft using a sequence of instantaneous frequency measurements from a single microphone, (ii) flight motion parameter estimation of a jet aircraft using the multipath time delay measurements from a single microphone located above the ground, and (iii) target motion parameter estimation of a ground vehicle using time difference of arrival measurements of its broadband radiated noise at pairs of microphones configured as a cross array. However, the results of processing acoustic sensor data using conventional methods such as time‐frequency analysis of narrowband signals and passive ranging by wavefront curvature of broadband signals show that both approaches to source parameter estimation are comparable. Conventional methods, which use basic data processing to extract source parameter information, are suited to implementation in embedded computers with limited data processing resources such as those found in networked wireless miniature sensing devices. Moreover, conventional methods can be used for initial estimation of the NLS parameter vectors.