 In ground static target detection, polarimetric high-resolution radar can distinguish the target from the strong ground clutter by reducing the clutter power in the range cell and providing additional polarimetric features. To address the difficulty of detecting multiple targets in one range cell, we propose a novel polarimetric range extended target, RET, detection method via adaptive range weighted feature extraction. We first extract polarimetric features of each range cell, then use a pre-trained attention mechanism to adaptively calculate range cell's weights, which are used to accumulate the range cell's features as detection statistics. While calculating weights, both amplitude and polarimetric features are taken into account. This method makes the most of polarization information and improves the accumulation effect, thus increasing the discrimination between targets and clutter. Our method has been tested against popular energy domain detection methods. Existing feature domain detection methods with promising results. Furthermore, we have analyzed our method on different target models and different clutter distributions, demonstrating its suitability for different types of targets and clutters. This article was authored by Mingcheng Yuan, Liang Zhang, Yanhua Wang, and others. We are article.tv, links in the description below.