An Algorithm Reused-Based Interference Cancellation With Mainlobe Maintenance Method

Radar serves as an essential sensor for detecting distant targets. However, under multiple mainlobe and sidelobe interferences, conventional interference suppression techniques often introduce significant distortion to the radar antenna's mainlobe, severely degrading critical performance metrics such as ranging and direction finding. An algorithm reused based interference cancellation with mainlobe maintenance method is proposed to solve this problem. First, a low-complexity method for estimating the direction of arrival (DOA) of interference is proposed. This method directly reuses the interference cancellation (IC) algorithm to compute the optimal weights, which are then used to synthesize the array pattern. The DOA of the interference is then estimated by identifying the null steering in this pattern. This approach eliminates the need for the computationally intensive eigenvalue decomposition, thereby significantly reducing the computational complexity. Second, based on the estimated interference DOA, a method for interference cancellation with mainlobe maintenance is introduced. By directly exploiting the estimated interference DOA information to construct a projection matrix, this method significantly reduces the computational complexity of the mainlobe maintenance. Additionally, through the projection of mainlobe interference energy onto the subspace associated with sidelobe interferences, it not only preserves the mainlobe integrity but also achieves improved suppression of sidelobe interferences. Finally, simulation and experimental results demonstrate the effectiveness of the proposed method.