By exploring the covariance structure information to reduce the uncertainty in adaptive processing, this paper presents a Persymmetric Modified Sample Matrix Inversion algorithm (PMSMI), together with the closed-form expressions of probabilities of detection and false larm. The new algorithm, which requires less computation and has a Constant False Alarm Rate (CFAR) feature, can significantly outperform the corresponding unstructured MSMI, especially in a severely non-stationary/non-homogeneous interference environment.
- Adaptive detection
- doubly symmetric covariance
ASJC Scopus subject areas
- Control and Systems Engineering
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering