Multi-parameter extraction and estimation method based on time-frequency contour for flapping-wing vehicle by laser micro-Doppler detection

Addressing the challenge of insufficient accuracy in extracting kinematic parameters of flapping-wing targets using current laser micro-Doppler detection methods, this paper proposes a parameter extraction and estimation method based on time-frequency contour analysis. The method first establishes an analytical micro-Doppler model of flapping-wing motion and reveals the mapping relationship between time-frequency spectral features and target parameters through numerical simulations. Then, by employing time-frequency contour analysis combined with a hybrid filtering approach using top-hat transform and singular value decomposition (SVD), the method accurately extracts key contour features such as peak frequency shift and crossing frequency shift from the time-frequency representation. Subsequently, parameters including flapping angle and wing length are retrieved. Compared with existing methods, the proposed approach achieves high-precision extraction of flapping frequency, flapping angle, and wing length. Under simulation conditions, the average relative errors for flapping angle and wing length are 2.19% and 3.43%, respectively; under 5 m experimental conditions, they are 6.30% and 6.75% (8.20% and 8.65% for 300 m condition). Compared with the previous error of 11%, the proposed method achieves a maximum improvement of 9% in flapping angle extraction accuracy. This study significantly enhances the estimation accuracy of micro-motion parameters of flapping-wing targets, providing a reliable theoretical and algorithmic foundation for laser micro-Doppler based recognition of flapping-wing targets.