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Although radar\u2013camera fusion provides complementary geometric and motion information, sparse and uncertain radar observations may introduce unreliable cues, while camera\u2013radar temporal asynchrony can further reduce cross-modal spatial consistency. To address these issues, this paper proposes Radar Prior and Time-Lag-Aware Quality-Adaptive Fusion (RPT-Fusion), a radar\u2013camera fusion framework that preserves the camera as the primary semantic modality while treating radar as a reliability-controlled auxiliary source. Sparse 4D radar measurements are transformed into probabilistic occupancy, density, velocity, and reliability priors, with direction-dependent spatial uncertainty represented through anisotropic radar-prior modeling. Local, global, and temporal quality estimates are then jointly used to regulate radar contributions during multi-scale feature fusion. In particular, the measured camera\u2013radar time lag is explicitly incorporated into both radar-prior construction and feature-level reliability control. Experiments on WaterScenes show that RPT-Fusion achieves 92.31% mAP50 at an Intersection-over-Union (IoU) threshold of 0.50 and 68.23% mAP50\u201395 averaged over IoU thresholds from 0.50 to 0.95, outperforming WS-DETR by 0.82 and 3.69 percentage points, respectively. Ablation experiments verify the contributions of radar-prior modeling, quality-adaptive fusion, and temporal quality, while repeated-training experiments show low performance variability. Time-lag analysis reveals condition-dependent benefits, with the largest observed improvement of 1.15 percentage points occurring when the camera\u2013radar offset reaches or exceeds 20 ms. Radar-frame-dropping experiments further show that mAP50 decreases from 92.31% to 91.54% when radar observations are progressively removed, indicating that the camera-centric pathway retains a substantial detection capability under incomplete radar observations. These results demonstrate the effectiveness of reliability-controlled radar assistance for robust radar\u2013camera object detection in complex water-surface environments.<\/jats:p>","DOI":"10.3390\/s26185860","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T13:50:27Z","timestamp":1789566627000},"page":"5860","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["RPT-Fusion: A Time-Lag-Aware Quality-Adaptive Radar\u2013Camera Fusion Framework for Water-Surface Object Detection"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1919-8673","authenticated-orcid":false,"given":"Yabin","family":"Xu","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0692-0186","authenticated-orcid":false,"given":"Sujie","family":"Zhan","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3359-4792","authenticated-orcid":false,"given":"Junnan","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"methodology","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9068-0227","authenticated-orcid":false,"given":"Weiming","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Science and Technology, Hong Kong Metropolitan University, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"resources","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7473-1146","authenticated-orcid":false,"given":"Honghua","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Data Science, Lingnan University, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"16584","DOI":"10.1109\/TITS.2024.3415772","article-title":"WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces","volume":"25","author":"Yao","year":"2024","journal-title":"IEEE Trans. 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