ASCRL evaluation with parametrically constrained covariance matrix

作者：Tan, Jie^*; Wang, Yikai; He, Zishu; Sun, Guohao

来源：Electronics Letters, 2018, 54(11): 718-+.

DOI：10.1049/el.2018.0423

• adaptive filters
• covariance matrices
• radar clutter
• adaptive radar
• maximum likelihood estimation
• radar detection
• two-step strategy
• constrained Cramer-Rao
• CCM estimate
• adaptive filter
• ASCRL evaluation
• parametrically constrained covariance matrix
• average signal-to-clutter ratio loss
• adaptive radar filter
• parametrically constrained clutter covariance matrix

In this Letter, the authors propose an approach to evaluate the average signal-to-clutter ratio loss (ASCRL) of an adaptive radar filter with a parametrically constrained clutter covariance matrix (CCM). The approach is a two-step strategy, the constrained Cramer-Rao bound of the CCM estimate is first derived, and then it is used to derive the ASCRL. More specifically, the ASCRL of an adaptive filter with a trace constrained CCM is derived. Simulation results show that our approach performs well in evaluating the trace constrained ASCRL for both complex Gaussian clutter and compound-Gaussian clutter.

• 出版日期2018-5-31
• 单位电子科技大学