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Considering the issues of large parameter count and memory occupation of the deep learning-based target detection models, a lightweight target detection method based on improved YOLOv4-tiny is proposed. The technique applies depthwise separable convolution (DSC) and bottleneck architecture (BA) to the YOLOv4-tiny network. Moreover, it introduces the convolutional block attention module (CBAM) in the improved feature fusion network. It allows the network to be lightweight while ensuring detection accuracy. We choose a certain number of pulses from the pulse-compressed radar data for clutter suppression and Doppler processing to obtain range\u2013Doppler (R\u2013D) images. Experiments are run on the R\u2013D two-dimensional echo images, and the results demonstrate that the proposed method can quickly and accurately detect dim radar targets against complicated backgrounds. Compared with other algorithms, our approach is more balanced regarding detection accuracy, model size, and detection speed.<\/jats:p>","DOI":"10.1007\/s11554-023-01316-5","type":"journal-article","created":{"date-parts":[[2023,5,27]],"date-time":"2023-05-27T03:31:18Z","timestamp":1685158278000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Deep learning-based lightweight radar target detection method"],"prefix":"10.1007","volume":"20","author":[{"given":"Siyuan","family":"Liang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4746-7997","authenticated-orcid":false,"given":"Rongrong","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Guodong","family":"Duan","sequence":"additional","affiliation":[]},{"given":"Jianbo","family":"Du","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,5,27]]},"reference":[{"issue":"4","key":"1316_CR1","doi-asserted-by":"publisher","first-page":"608","DOI":"10.1109\/TAES.1983.309350","volume":"AES-19","author":"H Rohling","year":"1983","unstructured":"Rohling, H.: Radar CFAR thresholding in clutter and multiple targets situation. 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