A Novel Insect Wingbeat Frequency Extraction Algorithm Based on Ambiguity Function

Accurate extraction of wingbeat frequency is crucial in insect radar for behavior analysis and species identification of migratory insects. However, the accuracy of extraction cannot be guaranteed due to the weak wingbeat signals and complex insect targets. To address this, this paper proposes an innovative method for enhancing insect wingbeat frequency extraction. This algorithm uses the periodic characteristics of wingbeat micro-motion signals to extract its delay frequency signal to locate its maximum value through the ambiguity function. Then, extract the insect wingbeat frequency by smoothing compensation and Fourier transform, which improves accuracy of insect wingbeat frequency extraction. The efficacy of our algorithm is validated through comprehensive simulations and field experiments, affirming its potential as a robust solution.