Showing 2 results for S. Sadri
S. Sadri, S. Gazor and A. M. Doosthoseini,
Volume 17, Issue 2 (4-1998)
Abstract
During the last two decades, Maximum Likelihood estimation (ML) has been used to determine Direction Of Arrival (DOA) and signals propagated by the sources, using narrowband array signals. The algorithm fails in the case of wideband signals. As an attempt by the present study to overcome the problem, the array outputs are transformed into narrowband frequency bins, using short time Fourier transform together with ML, to estimate DOA's and the signals. The effect of window parameters (i.e, type, length and decimation factor) on the bias and variance of estimation of DOA's and signals is investigated. The algorithm robustness and convergence in presence of low SNR and coherent signals is illustrated. It is also shown that the local optimal problem encountered in the narrowband case is resolved for the wideband signals.
H. Saeedi, M. Modarres-Hashemi and S. Sadri,
Volume 24, Issue 1 (7-2005)
Abstract
With progress in radar systems, a number of methods have been developed for signal processing and detection in radars. A number of modern radar signal processing methods use time-frequency transforms, especially the wavelet transform (WT) which is a well-known linear transform. The interference canceling is one of the most important applications of the wavelet transform. In Ad-hoc detection methods, the interference is firstly canceled and then a simple detector, like an energy detector, is
used. Therefore, we have used wavelet-based approaches to cancel the interference and then an energy detector has been employed. In this paper, it is shown that in practical cases where the performance of matched filter or near-matched filter is degraded, wavelet-based methods are more efficient. Also, we have shown that for cases where targets with slow radial velocity or one close to blind velocity are removed by the MTI filter, wavelet-based denoising has a better performance.
