tailieunhanh - 61 Beamforming Techniques for Spatial Filtering

Systems designed to receive spatially propagating signals often encounter the presence of interference signals. If the desiredsignal andinterferers occupy the same temporal frequency band, thentemporal filtering cannot be usedto separate signal frominterference. | Barry Van Veen et. Al. Beamforming Techniques for Spatial Filtering. 2000 CRC Press LLC. http . Beamforming Techniques for Spatial Filtering Barry Van Veen Uni vfWtynsin Kevin M. Buckley VllanoUniversity Introduction Basic Terminology and Concepts Beamforming and Spatial Filtering Second Order Statistics Beamformer Classification Data Independent Beamforming Classical Beamforming General Data Independent Response Design Statistically Optimum Beamforming Multiple Sidelobe Canceller Use of a Reference Signal Maximization ofSignal-to-Noise Ratio Linearly Constrained Minimum Variance Beamforming Signal Cancellation in Statistically Optimum Beamforming Adaptive Algorithms for Beamforming Interference Cancellation and Partially Adaptive Beamforming Summary Defining Terms References Further Reading Introduction Systems designed to receive spatially propagating signals often encounter the presence of interference signals. If the desired signal and interferers occupy the same temporal frequency band then temporal filtering cannot be used to separate signal from interference. However desired and interfering signals often originate from different spatial locations. This spatial separation can be exploited to separate signal from interference using a spatial filter at the receiver. A beamformer is a processor used in conjunction with an array of sensors to provide a versatile form of spatial filtering. The term beamforming derives from the fact that early spatial filters were designed to form pencil beams see polar plot in Fig. c in order to receive a signal radiating from a specific location and attenuate signals from other locations. Forming beams seems to indicate radiation of energy however beamforming is applicable to either radiation or reception of energy. In this section we discuss formation of beams for reception providing an overview of beamforming froma signal processing perspective. Data .