Space-time adaptive detection for bistatic MIMO system under covariance matrix persymmetry and symmetric spectrum

Abstract

Space-time adaptive detection (STAD) is an important research aspect of the bistatic multiple-input multiple-output (MIMO) radar system. The signal and clutter space-time models of the bistatic MIMO radar are described in this study. The knowledge-aided (KA) transform, which utilises the structural properties of the target-free data and the sample covariance matrix, is applied to increase the independent secondary data fourfold in the STAD frame. The performance assessment of the KA–STAD detectors with generalised likelihood ratio test (GLRT), adaptive matched filter (AMF), and Rao rules is presented. The simulation experiments show that the detection and constant false alarm rate performances of the presented KA–GLRT, KA–AMF, and KA–Rao detectors outperform the GLRT, AMF, and Rao detectors for the bistatic MIMO radar system STAD frame in clutter background with limited secondary data.

Keywords

• covariance matrices
• matched filters
• radar clutter
• space-time adaptive processing
• mimo radar
• radar detection
• signal detection
• transforms
• adaptive filters
• space-time adaptive detection
• bistatic mimo system
• covariance matrix persymmetry
• multiple-input multiple-output radar system
• clutter space-time models
• sample covariance matrix
• independent secondary data
• stad frame
• ka–stad detectors
• constant false alarm rate performances
• ka–rao detectors
• bistatic mimo radar system
• adaptive matched filter
• generalised likelihood ratio test
• knowledge-aided transform
• ka transform
• ka–amf detectors
• ka–glrt detectors