Title :
RLS design of polyphase components for the interpolation of periodically nonuniformly sampled signals
Author :
Vandendorpe, L. ; Maison, B. ; Cuvelier, L.
Author_Institution :
UCL Telecommun. & Remote Sensing Lab., Louvain-la-Neuve, Belgium
Abstract :
The generalized sampling theorem states that any analogue signal whose spectrum is limited to 1/T can be exactly recovered from N sequences of samples taken at a rate 2/NT and all having a different sampling phase. When N=2, the exact interpolation formula can be derived quite easily. The ideal interpolation filters have infinite impulse responses. This paper addresses the theoretical question of recovering from the 2 initial sequences, any other sequence taken at the some rate 1/T and with a different sampling phase. FIR filters are derived for a least square interpolation error. Moreover, an adaptive implementation is proposed and formulated as a Kalman algorithm. Simulation results obtained for AR processes show the effectiveness of the solution compared to static solutions
Keywords :
FIR filters; adaptive Kalman filters; adaptive signal processing; autoregressive processes; filtering theory; interpolation; least squares approximations; recursive filters; signal sampling; AR processes; FIR filters; Kalman algorithm; RLS design; adaptive filter; analogue signal; generalized sampling theorem; ideal interpolation filters; infinite impulse responses; interpolation; least square interpolation error; periodically nonuniformly sampled signals; polyphase components; sampling phase; simulation results; spectrum limited signal; Finite impulse response filter; Interpolation; Kalman filters; Laboratories; Least squares methods; Remote sensing; Resonance light scattering; Sampling methods; Signal design; Signal sampling;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.480460
