Aiming at the problem that the existing algorithms are difficult to extract fuzzy target features in the SAR image ship target detection scene, a ship target detection algorithm based on feature reuse pyramid is proposed. The proposed algorithm takes YOLOV4-tiny as the main body. First, a linear factor is introduced into the K-Means algorithm to integrate the initial anchor frame to enhance the adaptability of the network to multi-scale targets. Secondly, an attention mechanism is added to the backbone CSPDarknet53-tiny to suppress interference. information, and weaken the influence of complex background; finally, the feature reuse mechanism is used to strengthen the feature pyramid and improve the network's ability to extract fuzzy target features. The experimental results show that, compared with the YOLOV4-tiny network, the average detection accuracy of the improved algorithm on the SSDD dataset is improved by 11.79%, which proves the effectiveness of the improved algorithm in ship detection.