Spatial Directional Noise Cancelation and Weak Target Detection Method Based on Beamspace and Multiple Fourth-Order Cumulants for HFSWR

High-frequency surface wave radar (HFSWR) has been widely applied in early warning and marine remote sensing due to its over the horizon propagation characteristics. Noise and interference are the critical factors affecting its performance. However, as the detection environment of the system becomes increasingly harsh, the spatial distribution of external environ mental noise exhibits directional distribution characteristic, which is called directional noise. This type of anisotropic noise has complex behaviors, and its noise level in a specific direction is generally 10∼15dB higher than the background noise base, resulting in stealth targets, low radar scattering cross sectional (RCS) and low signal to noise ratio (SNR) targets are often submerged by it. Consequently, suppressing dynamic directional noise and detecting submerged targets have become new challenges for HFSWR. To address this, this paper proposes a spatial direction al noise suppression method for HFSWR based on beamspace with multiple fourth order cumulants (BSMFOC). First, we ana lyze the multidimensional characteristics of directional noise using measured data. Then, a simplified directional noise model is constructed based on array signal theory. Next, by integrating the spatial attributes and high order statistical characteristics of directional noise, multiple sample cumulants are constructed via selecting arbitrary orders and time delay quantities, and efficient noise suppression is achieved through multiple fourth order cumulant(FOC) processing. The simulation results verify the effectiveness of the method, and experimental analysis of actual directional noise data shows that it can significantly reduce the SNR required for target detection and exhibit excellent performance.