Abstract
Two automatic-frequency-control loops are introduced and analyzed in detail. The algorithms are generalizations of the well-known cross-product automatic-frequency-control loop with improved performance. The first estimator uses running overlapping discrete Fourier transforms (DFTs) to create a discriminator curve proportional to the frequency estimation error, whereas the second one preprocesses the received data and then uses an extended Kalman filter to estimate the input frequency. The algorithms are tested by computer simulations in a low carrier-to-noise-ratio (CNR) and highly dynamic environment. The algorithms are suboptimum tracking schemes with a larger frequency error variance compared to an optimum strategy, but they offer simplicity of mechanization and a CNR with a very low operating threshold.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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