Bounded Mapping Frequency Estimation Algorithm for Low SNR Environments

Frequency estimation plays a vital role in various research fields, such as Doppler compensation in wireless communication. Traditional DFT-based methods for frequency estimation often suffer from reduced performance under low-SNR conditions. In order to overcome this limitation, we present a novel non-iterative estimation approach that employs a bounded mapping strategy. By concentrating on the real part of the spectrum and constraining the frequency correction within a defined range, our method effectively mitigates inaccuracies caused by noise. Our proposed algorithm for frequency estimation achieves accuracy comparable to iterative methods while significantly reducing computational complexity. Through simulations and experiments, we illustrate that our approach enhances estimation accuracy at lower SNR levels with a limited number of samples compared to existing techniques.