## 3 The Results of the Bibliometric Analysis
### Citation and Co-Citation Network Analysis
#### 3.3.1 Publications Citation and Co-Citation Analysis
Furthermore, the distinctive colors assigned to these spheres denote their affiliation with specific clusters, signifying overarching thematic patterns prevalent within the research domain. The detailed setting for the parameters used for the figure is provided in Appendix A Table A2. Note that the total link strength within this network carries significant implications, as it reflects the cumulative intensity of connections between each unit. Notably, higher total link strength values signify closer inter-relationships with other units, underscoring their prominence within the co-citation framework. As illustrated in Figure 11, these 52 references were effectively partitioned into four distinct clusters based on their co-citation associations. The demarcation of these clusters served as a valuable analytical approach for explaining the primary research themes characterizing each group. This identification process drew upon a comprehensive analysis of the titles and abstracts of the references comprising these clusters, thus shedding light on the fundamental narrative patterns underpinning the discourse within the research community. The red cluster is the largest, with 16 references, primarily dedicated to the marine model control and control system. Within this cluster, the work titled \"Handbook of Marine Craft Hydrodynamics and Motion Control\", authored by [PERSON] [56] in 2011, emerged as the most frequently cited publication, with 26 citations, and exhibited  
Figure 11: Co-citation network of references cited more than seven times in USVs. the highest total link strength of 76, thus establishing its pivotal role as the central reference in this thematic cluster. The green cluster is the second largest cluster, with 14 references. This cluster emphasizes the overview of USVs, robot automation and visual remote sensing. The article \"Unmanned surface vehicles: An overview of developments and challenges\" by [PERSON] [2] in 2016 can be considered the core publication in this cluster, with the high citations (29) and total link strength (91), followed by the blue cluster with 12 references, primarily centered on the navigation and the neurocomputing application. Notably, the article titled \"COLREGs-based collision avoidance strategies for unmanned surface vehicles\", authored by [PERSON] et al. [57] in 2012, had the highest citation count at 13, and boasted the most substantial total link strength (78) within this cluster, thereby metriing recognition as the central reference shaping the discourse in this thematic group. Conversely, the smallest cluster, denoted by the color yellow and located at the right of the network, includes 10 references. The predominant themes in this cluster revolved around AI applications, such as deep learning, obstacle detection, object detection and autonomous visual perception. The article titled \"Stereo Vision-Based Navigation for Autonomous Surface Vessels\", authored by [PERSON] et al. [58] in 2011, occupied the central position within this cluster, marked by the highest citation count of 11 and the most significant total link strength of 34.