Adaptive CFAR detection for clutter-edge heterogeneity using Bayesian inference

Biao Chen, P.K. Varshney, J.H. Michels
2003 IEEE Transactions on Aerospace and Electronic Systems  
Radar constant false alarm rate (CFAR) detection is addressed in this correspondence. Motivated by the frequently encountered problem of clutter-edge heterogeneity, we model the secondary data as a probability mixture and impose a hierarchical model for the inference problem. A two-stage CFAR detector stucture is proposed. Empirical Bayesian inference is adopted in the first stage for training data selection followed by a CFAR processor using the identified homogeneous training set for target
more » ... ng set for target detection. One of the advantages of the proposed algorithm is its inherent adaptivity; i.e., the threshold setting is much less sensitive to the nonstationary environment compared with other standard CFAR procedures.
doi:10.1109/taes.2003.1261145 fatcat:jqpfejfkm5eofdnebi7y6zfypi