An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing

The article presents a new space-time adaptive processing (STAP) method for target detection in a heterogeneous and non-stationary environment. In study it was proven that it is possible to estimate the clutter covariance matrix (CCM) in STAP by using the MIMO (Multiple Input Multiple Output) radar...

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Bibliographic Details
Main Authors: Anna Ślesicka, Adam Kawalec
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/12/3468
Description
Summary:The article presents a new space-time adaptive processing (STAP) method for target detection in a heterogeneous and non-stationary environment. In study it was proven that it is possible to estimate the clutter covariance matrix (CCM) in STAP by using the MIMO (Multiple Input Multiple Output) radar geometry model and the orthogonal matching pursuit (OMP) algorithm. For the estimation of spatio-temporal spectrum of clutter and target, a model of joint sparse recovery was established. As a result, clutter suppression and target detection in a heterogeneous environment will be achieved. In addition, the proposed method uses a single snapshot of the radar data cube, which eliminates the need for access to all training cells.
ISSN:1424-8220