Abstract: Aiming at the problem that the sample covariance can not replace the statistical covariance when the
number of samples is small，a novel target detection method based on Riemannian manifold is proposed for
monostatic MIMO( Multiple-Input Multiple-Output) radar． It takes advantage of the fact that the THPD( Toeplitz-
Hermitian Positive Definite) matrix can form Riemannian manifold in signal space． The single-snapshot THPD
covariance matrices of received signals and noises are respectively generated through the burg algorithm，and the
Riemannian mean of the noise THPD covariance matrices is calculated． The Riemannian distance between the
THPD covariance matrices of received signal and noise is taken as the detection statistic． The method can
increase the dissimilarity between the received signal and noise on the Riemannian manifold． The simulation
results indicate that compared to the traditional method which uses the Euclidean distance，the proposed method
can significantly improve the target detection performance under low SNR ( Signal-to-Noise Ratio) and singlesnapshot．

Key words: radar engineering, target detection, riemannian manifold, burg algorithm