Exploiting Covariance Structure for Signal Detection in Array Processing
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Array processing involves utilizing multiple sensors (e.g., antennas) to collect data from a spatial environment. The primary objective is to extract the desired signal from a mixture of noise and interference. Several techniques exist for signal detection, including beamforming, matched filtering, and likelihood ratio tests. These methods typically rely on assumptions about the signal and noise characteristics. However, real-world environments often violate these assumptions. Noise may not be purely white (uncorrelated) and can exhibit spatial coherence. Additionally, interference might be structured and non-stationary. Here's where exploiting the covariance structure of the received data becomes advantageous.
Format:Paperback
Language:English
ISBN:3384276647
ISBN13:9783384276643
Release Date:July 2024
Publisher:Tredition Gmbh
Length:108 Pages
Weight:0.37 lbs.
Dimensions:0.3" x 6.0" x 9.0"
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