# Time Delay Optimization of Compressing Shipborne Radar Digital Video Based on Deep Learning
## 1 Introduction  
In recent years, various automation technologies centered on unmanned ships have developed rapidly. The observation of shipborne radar digital video is the most intuitive and efficient way to understand the navigation state of the target ship. Optimizing the transmission and storage of radar data has become a popular topic in the field of unmanned ship research. Data compression technology, as the basis of ship-to-shore intelligent information interaction, is also a key technology of unmanned ship remote control. The International Convention for the Safety of Life at Sea (SOLAS) requires that ships of 500 gross tonnage (GT) and above should be equipped with radar devices, and ships of 10,000 GT and above should be fitted with two independent radar devices; furthermore, the radar devices should be able to operate at 9 GHz frequency [17]. The main data to be used in the future, such as driving video and radar digital images of unmanned ships, need to be compressed and transmitted to intelligent equipment for processingand storing, under the condition of limited maritime bandwidth. Thus, it is necessary to improve the efficiency of compression of the algorithm to reduce delay. As shown in Figure 17, for the purpose of realizing remote virtual driving of an unmanned ship, the data generated by various devices on ships need to be shared in real time with other devices and shore-based consoles to monitor the current performance status of the ship, and simulate and create a real ship bridge environment. As the most important piece of equipment to assist ships in safe navigation and collision avoidance, shipborne radar is mainly responsible for indicating the position between the ship and objects, strengthening the awareness in real-time traffic situations, and assisting the ship in judging encounters. The International Maritime Organization (IMO) requires that when a ship is sailing along a coast or in a port, the shipborne radar digital video needs to show clear shorelines and the location of other fixed dangerous objects. In collision avoidance operations, shipborne radar needs to provide the pilot with the detection of nearby hazardous targets and the position information of obstacles relative to the ship. This is obtained according to a report to help the ship make decisions and verify the effectiveness of collision avoidance action [2 ]. IMO also stipulates that shipborne radar must be able to detect small buoys, including fixed navigation beacons and hazards, for safe navigation and collision avoidance [2 ]. Therefore, the speed and code rate of compressing shipborne radar digital video not only determines the transmission efficiency, but also affects the safety of the ship under remote control. Since the 1980s, in order to solve the problem of large-scale intercommunication and transmission of video images, the International Telecommunication Union for Telecommunication Standardization Sector (ITU-T) and the International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) jointly issued the H.26x series of video coding standards [2 ]. In 2013, the Joint Collaborative Team on Video Coding (JCT-VC) issued the high efficiency video coding standard (H.265/HEVC), which is mainly applied to ultra-high-definition digital video, and released the expansion scheme of screen content coding (HEVC-SCC) [2 ]. In 2016, Intra Block Copy (IBC) [2 ], Palette Mode (PLT) [2 ], Adaptive Color Transform (ACT) [2 ], Adaptive Motion Vector Resolution (AMVR) [2 ], etc., were added. The above technology has further improved the performance of encoding digital screen video. Although the introduction of new technologies is dedicated to improving coding quality and coding efficiency, it has also led to increasing computational complexity. In the optimal dividing process of determining the Coding Tree Unit (CTU), HEVC introduces a new segmentation structure, which increases its code rate  
Figure 1: Schematic diagram of remote transmission of radar video.