Discrete-time signal processing
Discrete-time signal processing
The SVD and reduced rank signal processing
Signal Processing - Theme issue on singular value decomposition
Matrix computations (3rd ed.)
Handbook of Digital Signal Processing: Engineering Applications
Handbook of Digital Signal Processing: Engineering Applications
Cramér-Rao lower bounds for the synchronization of UWB signals
EURASIP Journal on Applied Signal Processing
Prefiltering-based ESPRIT for estimating sinusoidal parameters innon-Gaussian ARMA noise
IEEE Transactions on Signal Processing
Joint angle and delay estimation using shift-invariance techniques
IEEE Transactions on Signal Processing
Time delay and spatial signature estimation using knownasynchronous signals
IEEE Transactions on Signal Processing
Optimal reduced-rank estimation and filtering
IEEE Transactions on Signal Processing
Channel estimation for ultra-wideband communications
IEEE Journal on Selected Areas in Communications
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We investigate reduced-rank shift-invariant technique and its application for synchronization and channel identification in UWB systems. Shift-invariant techniques, such as ESPRIT and the matrix pencil method, have high resolution ability, but the associated high complexity makes them less attractive in real-time implementations. Aiming at reducing the complexity, we developed novel reduced-rank identification of principal components (RIPC) algorithms. These RIPC algorithms can automatically track the principal components and reduce the computational complexity significantly by transforming the generalized eigenproblem in an original high-dimensional space to a lower-dimensional space depending on the number of desired principal signals. We then investigate the application of the proposed RIPC algorithms for joint synchronization and channel estimation in UWB systems, where general correlator-based algorithms confront many limitations. Technical details, including sampling and the capture of synchronization delay, are provided. Experimental results show that the performance of the RIPC algorithms is only slightly inferior to the general full-rank algorithms.