Abstract
Research in the field of efficient frequency estimation algorithms is of great interest. The reason for this is the redistribution of the role of additive and phase noise in many modern radio-engineering applications. An example is the area of measuring radio devices, which usually operate at high signal-to-noise ratios (SNR). The estimation error is largely determined not by the broadband noise, but by the frequency and phase noise of the local oscillators of the receiving and transmitting devices. In particular, earlier works \\cite{Nikiforov} proposed an efficient computational algorithm for estimating the frequency of a quasi-harmonic signal based on the iterative calculation of the autocorrelation sequence (ACS). In \\cite{Volkov}, this algorithm was improved and its proximity to the Rao-Cramer boundary was shown (the sources of this noise are master oscillators and frequency synthesizers). Possibilities of frequency estimation in radio channels make it possible to significantly expand the functionality of the entire radio network. This can include, for example, the problem of adaptive distribution of information flows of a radio network. This also includes the tasks of synchronization and coherent signal processing. For these reasons, more research is needed on this algorithm, the calculation of theoretical boundaries and their comparison with the simulation results.
Highlights
Research in the eld of e cient frequency estimation algorithms is of great interest. e reason for this is the redistribution of the role of additive and phase noise in many modern radio-engineering applications
An example is the area of measuring radio devices, which usually operate at high signal-to-noise ratios (SNR). e estimation error is largely determined not by the broadband noise, but by the frequency and phase noise of the local oscillators of the receiving and transmi ing devices
Earlier works [1] proposed an e cient computational algorithm for estimating the frequency of a quasi-harmonic signal based on the iterative calculation of the autocorrelation sequence (ACS)
Summary
Модель комплексного сигнала на выходе канала с АБГШ и фазовым шумом можно записать в виде ( ) = exp ( [2 0 + ( )]) + ̇ ( ), где – время; – амплитуда; 0 – номинальная частота; ( ) – фазовая функция сигнала; ̇ ( ) – АБГШ. Δ ( ) = 0 − ̂( ), Δ ( ) = ( ) − ̂( ), где( ), ̂( ) – фактические мгновенные значения частоты и фазы сигнала. Частотные и фазовые шумы генераторов характеризуются следующими функциями [3, 4]: – спектральная плотность фазовых флуктуаций ( )=. Общепризнанной моделью представления спектральной плотности фазовых и частотных флуктуаций является степенная модель [3]:. В таблице 1 представлена классификация основных частотных и фазовых шумов генераторов [3, 4].
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