Performance of knowledge aided space time adaptive processing

• Published in: IET radar, sonar & navigation Vol. 5; no. 3; pp. 331 - 340
• Main Authors: Tang, B., Tang, J., Peng, Y.
• Format: Journal Article
• Language: English
• Published: Stevenage Institution of Engineering and Technology 01.03.2011; The Institution of Engineering & Technology
• Subjects: Applied sciences; Asymptotic properties; Colour; Covariance matrix; Exact sciences and technology; Information, signal and communications theory; Mathematical analysis; Matrix theory; Miscellaneous; Navigation; Signal processing; Steering; Telecommunications and information theory; Vectors (mathematics); Performance evaluation; Monte Carlo method; Random matrix; Space-time adaptive processing; A priori estimation; Signal processing; Eigenvalue; Numerical simulation; Covariance matrix; Signal to interference plus noise ratio
• ISSN: 1751-8784; 1751-8792
• DOI: 10.1049/iet-rsn.2010.0131

In this study, the asymptotic average signal-to-interference plus noise ratio (SINR) loss of knowledge-aided (KA) space time adaptive processing (STAP) is derived based on the random matrix theory. The authors observe that the desired steering vector and a priori covariance matrix is whitened by the covariance matrix of cell under test. An important result in this study is that one finds the SINR loss of KA STAP can be factorised into two parts. The first part of SINR loss is determined by the number of independent and identically distributed secondary samples, system degree of freedom, colour loading level and the eigenvalues of whitened a priori covariance matrix. The angle between two vectors accounts for the second part of SINR loss, where the first vector is the whitened desired steering vector, the second vector is a rotated version of this whitened vector with the rotation matrix equal to whitened a priori covariance matrix.