Robust statistical recognition and reconstruction scheme based on hierarchical Bayesian learning of HRR radar target signal

作者：

Highlights：

• We develop a Bayesian model for complex data of high range resolution (HRR) radar.

• A recognition scheme robust to noise and narrowband interference is proposed.

• A statistical compressive sensing inversion is derived for recovery of HRR data.

• Efficient inference is performed via variational Bayesian.

• Experimental results show our methods perform better than some existing methods.

摘要

•We develop a Bayesian model for complex data of high range resolution (HRR) radar.•A recognition scheme robust to noise and narrowband interference is proposed.•A statistical compressive sensing inversion is derived for recovery of HRR data.•Efficient inference is performed via variational Bayesian.•Experimental results show our methods perform better than some existing methods.

论文关键词：Hierarchical Bayesian learning,Compressive sensing,Radar automatic target recognition (RATR),High range resolution (HRR) radar,Markov dependency

论文评审过程：Available online 8 April 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.03.029