High precision time and frequency difference of arrival estimation in complex electromagnetic environments

Conventional time and frequency difference of arrival estimation methods often deteriorate severely in complex electromagnetic environments, particularly in the presence of co-channel interference. To address this challenge, a high precision time and frequency difference of arrival estimation method is proposed based on spectral filtering and cyclic correlation. In the proposed method, the received signals are first converted into the frequency domain, where the spectral filtering method is applied to remove the interferences from other channels. Sequentially, the cyclic frequency values of the processed signals are calculated using the strip spectral correlation algorithm (SSCA) to differentiate the signal of interest (SOI) from co-channel interferences. The alpha-cross ambiguity function (α-CAF) is then constructed based on the cyclic frequency of SOI. Finally, a two-step approach including a coarse search for the peak of α-CAF followed by a fine search, is utilized to quickly obtain the time and frequency difference of arrival for SOI. The effectiveness of the proposed method is validated by numerical simulations.