Land Clutter

Land clutter, unwanted signals obscuring targets in radar imagery, is a significant challenge in various applications, particularly target detection. Current research focuses on improving clutter classification and target detection algorithms, employing techniques like deep learning architectures (e.g., RepVGG, GANs) and advanced signal processing methods (e.g., wavelet transforms) to enhance accuracy and efficiency. These advancements are crucial for improving the performance of radar systems in diverse environments, from maritime surveillance to remote sensing, by enabling more reliable target identification amidst complex background noise.