Vehicle Detection in High-Resolution Polsar Images Via GP-PNF Distribution Modeling
Jie Deng, Wei Wang, Huiqiang Zhang, Sinong Quan, Jun Zhang · 2024
Vehicle detection is an important application of polarimetric synthetic aperture radar (PolSAR). Geometrical perturbation polarimetric notch filter (GP-PNF) establishes a feature space based on the local background polarimetric characteristics to achieve adaptive detection of ship targets. However, the complexity of the ground background presents additional challenges compared to sea surface. In this work we model the distribution of the GP-PNF and prove its effectiveness and accuracy compared with other common distribution models based on real airborne mini-SAR data. And then we introduce a numerical calculation of logarithm cumulants for parameters estimation, derive the constant false alarm rate (CFAR) threshold computation formula and apply the filter to vehicle detection. Experiments performed on real high-resolution PolSAR images verify the good performance of the detection method.