In this letter, a transmit waveform covariance matrix design method based on the first null constraint is proposed for the transmit beampattern design of Multiple-Input Multiple-Output radar. This method effectively concentrates more transmit energy within the beam, thereby enhancing the detection capability of radar. Additionally, considering the presence of steering vector errors in the radar transmit array, a robust waveform design method under the same constraint is also proposed. Finally, simulation experiments demonstrate the effectiveness of the proposed method.

To address the challenge of identifying true and false targets for non-cooperative passive radar (NPR) under distance deception jamming, this letter proposed a recognition method based on mutual information entropy (MIE) by combining the concept of entropy in information theory. By establishing a reference motion model as an intermediary, target measurements are transformed into the MIE dimension, where Bayesian methods are applied to establish a decision model solved via Gibbs sampling for target discrimination. This method efficiently identifies target trace points with limited measurement data and is better suited for NPR systems with unknown illuminator information compared to traditional anti-jamming methods that require multidimensional signal features. The effectiveness has been validated through simulation results.