Adaptive Clutter Suppression Method for Target Detection in Clutter Region

The rapid growth of consumer-grade unmanned aerial vehicles (UAVs) not only brings convenience to people's life, but also poses risks to the public safety. Thus, effective low-altitude regulatory measures are urgently needed to respond to such situation. With advantages of no signal transmitting, less maintenance, and low operation costs, passive radars become an important means for low-altitude surveillance. In the passive detection, echo signals of UAVs are prone to entering clutter region and being obscured by clutters due to their characteristics of low flying height, slow speed, and small sizes, which challenges the clutter suppression and signal detection. To tackle this problem, an adaptive clutter suppression method based on successive cancellation for target detection in clutter region is proposed in this paper. By taking advantage of the time-invariant characteristic of clutter spectrum peak and the time-variant characteristic of target spectrum peak, this method transforms the range migration problem in conventional researches into a helper of target identification in clutter region, and thus achieves the purpose of adaptively identifying strong clutters from multi-frames detection data and suppressing them as well as protruding the target in clutter region, which lays the foundation for further target detection. Experimental results based on simulated data show that the proposed method can effectively suppress strong clutters and protrude the weak target in clutter region, which validates the feasibility and effectiveness of the proposed method.