In this paper, we address the problem of robust waveform optimization with imperfect clutter prior knowledge to improve the worst-case detection performance of multi-input multi-output (MIMO) space-time adaptive processing (STAP) in the presence of colored Gaussian disturbance. An iterative algorithm is proposed to optimize the waveform covariance matrix (WCM) for maximizing the worst-case output signalinterference-noise-ratio (SINR) over the convex uncertainty set such that the worst-case detection performance of MIMO-STAP can be maximized. By exploiting the diagonal loading (DL) method, each iteration step in the proposed algorithm can be reformulated as a semidefinite programming (SDP) problem, which can be solved very efficiently. Numerical examples show that the worst-case output SINR of MIMO-STAP can be improved considerably by the proposed method compared to that of uncorrelated waveforms.Index Terms-MMO-STAP, robust waveform design, diagonal loading, semidefinite programming.
By inversion calculation of T2 spectrum of echo string, the permeability, saturation, fluid type and other important parameters of porous media can be obtained. However, since the inversion algorithm itself is susceptible to noise signal [1], improving the SNR level of echo signal has been one of the key problems in the application of low-field NMR technology. In order to obtain more accurate analysis results, the corresponding noise reduction method needs to be developed. In the past, the research on noise reduction of NMR signal mainly focused on echo string. This paper constructs a complete NMR signal model and discusses the de-noising of echo and echo string. Aiming at noise reduction of echo, FIR filter and Orthogonal Modulation Filter(OMF) are discussed. Aiming at the de-noising of echo string, this paper proposes an improved CEEMD threshold de-noising, and makes a comparative analysis with the heuristic threshold de-noising based on sym4 wavelet and EMD threshold de-noising proposed by predecessors. It is found that the method proposed in this paper can invert the more accurate T2 spectrum while improving the SNR.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.