A Cascade-filtered Adaptive CFAR Detector in Low Small Target Detecting

In the context of detecting low-flying small targets in urban high-rise environments, the targets are often obscured by large clutter reflectors or non-uniform clutter regions. This paper proposes a cascaded filtering adaptive constant false alarm rate (CFAR) detector. This method consists of two cascaded detectors. Units judged as "target present" by the first stage are filtered out in the second stage. Compared to single-stage detectors, this method effectively integrates the performance advantages of multiple CFAR techniques. This makes it suitable for more complex detection environments. Based on measured data and Monte Carlo simulation results, the cascaded filtering CFAR detector has a high detection rate in multi-target environments and a low false alarm rate in non-uniform clutter edge environments.