Fractal functions and wavelet expansions based on several scaling functions
Journal of Approximation Theory
Digital Communication Receivers: Synchronization, Channel Estimation, and Signal Processing
Digital Communication Receivers: Synchronization, Channel Estimation, and Signal Processing
Microwave Mobile Communications
Microwave Mobile Communications
Array Signal Processing: Concepts and Techniques
Array Signal Processing: Concepts and Techniques
Blind multiband signal reconstruction: compressed sensing for analog signals
IEEE Transactions on Signal Processing
Compressed sensing of analog signals in shift-invariant spaces
IEEE Transactions on Signal Processing
Sampling theorems for signals from the union of finite-dimensional linear subspaces
IEEE Transactions on Information Theory
Robust recovery of signals from a structured union of subspaces
IEEE Transactions on Information Theory
Uncertainty relations for shift-invariant analog signals
IEEE Transactions on Information Theory
Subspace methods for the blind identification of multichannel FIRfilters
IEEE Transactions on Signal Processing
Sampling Moments and Reconstructing Signals of Finite Rate of Innovation: Shannon Meets Strang–Fix
IEEE Transactions on Signal Processing
A Theory for Sampling Signals From a Union of Subspaces
IEEE Transactions on Signal Processing
Sampling signals with finite rate of innovation
IEEE Transactions on Signal Processing
Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors
IEEE Transactions on Signal Processing - Part I
IEEE Transactions on Information Theory
DS-CDMA synchronization in time-varying fading channels
IEEE Journal on Selected Areas in Communications
Characterization of ultra-wide bandwidth wireless indoor channels: a communication-theoretic view
IEEE Journal on Selected Areas in Communications
Recovering signals from lowpass data
IEEE Transactions on Signal Processing
Block-sparse signals: uncertainty relations and efficient recovery
IEEE Transactions on Signal Processing
The Cramér-Rao bound for estimating a sparse parameter vector
IEEE Transactions on Signal Processing
Subsample time delay estimation of chirp signals using FrFT
Signal Processing
Hi-index | 35.69 |
Time-delay estimation arises in many applications in which a multipath medium has to be identified from pulses transmitted through the channel. Previous methods for time delay recovery either operate on the analog received signal, or require sampling at the Nyquist rate of the transmitted pulse. In this paper, we develop a unified approach to time delay estimation from low-rate samples. This problem can be formulated in the broader context of sampling over an infinite union of subspaces. Although sampling over unions of subspaces has been receiving growing interest, previous results either focus on unions of finite-dimensional subspaces,or finite unions. The framework we develop here leads to perfect recovery of the multipath delays from samples of the channel output at the lowest possible rate, even in the presence of overlapping transmitted pulses, and allows for a variety of different sampling methods. The sampling rate depends only on the number of multi-path components and the transmission rate, but not on the bandwidth of the probing signal. This result can be viewed as a sampling theorem over an infinite union of infinite dimensional subspaces. By properly manipulating the low-rate samples, we show that the time delays can be recovered using the well-known ESPRIT algorithm. Combining results from sampling theory with those obtained in the context of direction of arrival estimation, we develop sufficient conditions on the transmitted pulse and the sampling functions in order to ensure perfect recovery of the channel parameters at the minimal possible rate.