Narrow Results

This paper links the joint time delay and frequency estimation problem to the data model with shift invariance characteristics. A novel method for joint time delay and frequency estimation of sinusoidal signals received at multiple separated sensors is derived. The proposed algorithm takes advantage of multi-invariance characteristic to estimate frequency and also employs single invariance property to estimate time delay. The algorithmic performance is shown to be better than both ESPRIT method and state-space realization algorithm. Simulation results illustrate performance of this algorithm.

The vibrational acoustic signals collected on pipelines contain substantial information concerning the working status of pipelines. They can be used for pinpointing leaks in buried pipelines. However, because of the complexity of signal composition and the heavy corruption of signals by ambient noises, it is essential to set up an appropriate signal model and scheme of analysis and synthesis in order to extract leak signatures and specify leak locations. In addition, the features of vibrational acoustic signals vary with materials, sizes and buried conditions of tubular pipes. It is difficult to pre-determine the knowledge of signals, such as the spectral knowledge. Here, an adaptive detection and estimation strategy is proposed based on LMS adaptive filtering and modified Wavelet denoising. The feasibility leak detection and location estimation is first automatically analysed by the signal processing procedure without any prerequisite on signals and then the procedure adaptively finds better estimate. With the proposed schemes, even where collected signals are heavily blurred by bursting interferences and present non-stationary, the instrument may also carry on detection and achieve effective results.