LAUSR

Aiming at the problem of low detection ability and low signal‐to‐noise ratio of infrared light screens under strong background light conditions, this paper proposes a denoising and recognition matching method of projectile signal in infrared light screens based on HOA‐VMD under strong background light conditions. It combines the hiking optimization algorithm (HOA) and the variational mode decomposition (VMD) to decompose the signal and extract the effective components, then the wavelet layered threshold function is used for multi‐scale denoising to effectively filter out the noise interference of the strong background light. Based on the theoretical velocity of the flying projectile, the dynamic time warping (DTW) algorithm is used to recognize and match the multi‐target signals, and the performance of the infrared light screens is improved. The experimental results show that this method can effectively improve the processing accuracy of infrared light screens signal under strong background light conditions. Compared with the existing VMD denoising, EMD denoising, wavelet soft threshold denoising and wavelet hard threshold denoising methods, the signal‐to‐noise ratio is increased by 24.05%, 36.09%, 43.67%, and 48.46%, respectively. It can accurately eliminate the interference signal and retain the real projectile signal.