Sparse covariance-based high resolution time delay estimation for spread spectrum signals

A new approach to time delay estimation for spread spectrum signals which is based on a covariance-based fitting criterion is introduced. Since the conventional correlation method cannot resolve the spread spectrum signals that are separated less than a pseudo-noise chip apart, a further process may be necessary for correlation outputs to increase the resolution capability. To this end, a sparse covariance-based estimation algorithm that was originally proposed for direction-of-arrival estimation is adopted and its superiority is verified, especially in correlated signal environments.