Impulse Response Estimation via Laguerre-Fourier Expansion
Tamás Dózsa, Art J. R. Pelling, Matthias Voigt
Abstract
The empirical transfer function estimate (ETFE) is a widely used method for system identification of linear time-invariant (LTI) systems in engineering disciplines such as acoustics, audio engineering, seismography, and tomography. However, ETFE suffers from numerical limitations when the excitation signal is band-limited or vanishes at certain frequencies, which is a common physical constraint of the excitation in practice. In such cases, division in the frequency domain becomes heavily ill-conditioned, and small measurement disturbances or numerical inaccuracies can degrade the solution. This paper presents L-ETFE, a generalization of ETFE based on Laguerre-Fourier expansions that addresses these limitations. After a suitable transformation, the method can yield a well-conditioned circulant problem even when the original ETFE system is ill-conditioned. Solving this problem via classical ETFE yields the discrete Laguerre-Fourier coefficients of the system's transfer function. The desired impulse response (IR) of the system-to-be-identified can then be recovered by a subsequent transformation pipeline. We derive novel and efficient algorithms for performing these transformations and analyse the conditioning of the transformed problem, explicitly characterizing its dependence on the input and a parameter used in the Laguerre-Fourier expansion. We evaluate the method on two simulated discrete-time LTI systems of varying complexity. The experiments demonstrate accurate IR recovery for spectral-zero and band-limited excitation, where standard ETFE fails.
Create a lesson
Related papers
From Multimode Near-Field Coupling to Friis
Mats Gustafsson
Distributed Sensing on a 110-kV Overhead-Line Maintenance Operation on an Operational Optical Ground Wire
Konstantinos Alexoudis, Torm Järvelill, Hendrik Johann Kerm et al.
Stable Filters for Generative Modeling of Graph Signals
Martin Schmidt, Gonzalo Mateos
Learning Array Signal Topologies as Conditional Neural Manifolds
Julian P. Merkofer, Vincent van de Schaft, Ruud J. G. van Sloun
QUBO Formulations of the Downlink MIMO Scheduling Problem in 5G Base Stations
Olli Apilo, Jorma Kilpi
Massive MIMO ISAC Under Target-Angle Uncertainty: CRLB Outage Analysis and Robust Resource Allocation
Smriti Uniyal, Tianyu Fang, Van-Dinh Nguyen et al.