LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles.
Sign Up to like articles & get recommendations!
RFI Mitigation for UWB Radar Via Hyperparameter-Free Sparse SPICE Methods
Radio frequency interference (RFI) causes serious problems to ultrawideband (UWB) radar operations due to severely degrading radar imaging capability and target detection performance. This paper formulates proper data models and… Click to show full abstract
Radio frequency interference (RFI) causes serious problems to ultrawideband (UWB) radar operations due to severely degrading radar imaging capability and target detection performance. This paper formulates proper data models and proposes novel methods for effective RFI mitigation. We first apply the single-snapshot Sparse Iterative Covariance-based Estimation (SPICE) algorithm to data from each pulse repetition interval for RFI mitigation and discuss the connection of SPICE to the $l_{1}$ -penalized least absolute deviation ($l_{1}$ -PLAD) approach. Then, we devise a modified group SPICE algorithm and we prove that it is equivalent to a special case of the $l_{1,2}$ -PLAD method. The modified group SPICE algorithm can be applied to data from a coherent processing interval for effective RFI mitigation. Both the single-snapshot SPICE and the modified group SPICE methods simultaneously exploit the sparsity properties of both RFI spectrum and UWB radar target echoes. Unlike the existing sparsity-based RFI suppression methods, such as the robust principal component analysis algorithm, the proposed methods are hyperparameter-free and therefore easier to use in practical applications. Furthermore, the fast implementation of the SPICE methods is considered by exploiting the special structures of both single-snapshot and multiple-snapshot covariance matrices. Finally, the results obtained from applying the SPICE methods to simulated data as well as measured data collected by the U.S. Army Research Laboratory synthetic aperture radar system are presented to demonstrate the effectiveness of the proposed methods.
Share on Social Media:
  
        
        
        
Sign Up to like & get recommendations! 1
Related content
More Information
            
News
            
Social Media
            
Video
            
Recommended
               
Click one of the above tabs to view related content.