A novel detection method for warhead fragment targets in optical images under dynamic strong interference environments

A measurement system for the scattering characteristics of warhead fragments based on high-speed imaging systems offers advantages such as simple deployment, flexible maneuverability, and high spatiotemporal resolution, enabling the acquisition of full-process data of the fragment scattering process. However, mismatches between camera frame rates and target velocities can lead to long motion blur tails of high-speed fragment targets, resulting in low signal-to-noise ratios and rendering conventional detection algorithms ineffective in dynamic strong interference testing environments. In this study, we propose a detection framework centered on dynamic strong interference disturbance signal separation and suppression. We introduce a mixture Gaussian model constrained under a joint spatial-temporal-transform domain Dirichlet process, combined with total variation regularization to achieve disturbance signal suppression. Experimental results demonstrate that the proposed disturbance suppression method can be integrated with certain conventional motion target detection tasks, enabling adaptation to real-world data to a certain extent. Moreover, we provide a specific implementation of this process, which achieves a detection rate close to 100% with an approximate 0% false alarm rate in multiple sets of real target field test data. This research effectively advances the development of the field of damage parameter testing.