ADAPTIVE TIME-DELAY ESTIMATION IN NONSTATIONARY SIGNAL AND OR NOISE POWER ENVIRONMENTS

A new model for an adaptive time-delay estimator is proposed to improv e its performance in estimating the difference in arrival time of a ba nd-limited random signal received by two spatially separated sensors i n an environment where the signal and/or noise power are time varying. The system comprises two adaptive units, a filter to compensate time shift between the two receiver channels, and a gain control to provide Wiener filtering. Both the filter coefficients and the variable gain are adjusted simultaneously by using modifications from the stochastic mean square error gradient in the traditional adaptive least mean squ are time-delay estimation (LMSTDE) method. The convergence characteris tics of the proposed system are analyzed in detail and comparison with the traditional technique is performed. Theoretical results show that , unlike the LMSTDE configuration, this arrangement can decouple the a daptation of time shift from the changing signal and/or noise power, w hich in turn gives rise to a better convergence behavior of the delay estimate. The proposed adaptive model has another advantage in that th e steady state variance of delay estimate can be assessed from time to time during adaptation, which is difficult to achieve in the traditio nal method when the signal and/or noise power are unavailable or time varying. Simulation results are included to illustrate the effectivene ss of the new model and corroborate the theoretical developments.