An Intelligent Sample Selection Method for Space-Time Adaptive Processing in Heterogeneous Environment

Space-time Adaptive Processing (stap) for Low Sample Support Applications

Airborne radar Space-Time Adaptive Processing (STAP) in a heterogeneous, target-rich environment is addressed. An efficient Kalman Filter implementation of the normalized form of the Parametric Adaptive Matched Filter (NPAMF) is introduced and shown to perform well against a detailed simulation of a site-specific, dense-target environment, Ground Moving Target Indication (GMTI) scenario. The nu...

intelligent mcdm method for supplier selection under fuzzy environment

supplier evaluation and selection is complex which caused by the dynamic and fuzzy environment. current mcdm methods do not consider the nature of the environment that can affect the process of evaluation and ranking. the aim of this study is to propose a dynamic fuzzy hybrid mcdm method for evaluation, ranking and selection. the proposed method employs fuzzy analytic hierarchy process (fahp) f...

Sample-by-sample adaptive space-time processing for multiuser detection in multipath CDMA systems

Multiuser detection and space-time processing are two advanced signal-processing techniques for the mitigation of multiple-access interference and intersymbol interference in wireless CDMA communications. The purpose of this work is to investigate techniques for efficient space-time multiuser detection (ST MUD). A companion paper considered batch iterative methods, which assume knowledge of all...

Space-time adaptive processing

Space-Time Adaptive Processing: Fundamentals

In this lecture, we present the principles of space-time adaptive processing (STAP) for radar, applied to moving target indication. We discuss the properties of optimum STAP, as well as problems associated with estimating the adaptive weights not encountered with spatial-only processing (i.e. beamforming).