# A Novel Ship-Tracking Method for GF-4 Satellite Sequential Images
## 1 Introduction  
The geostationary orbit (GEO) remote sensing satellite has become a very important aspect of current remote sensing areas because of its advantage of wide-swath scanning, near real-time continuous observation and rapid operational response, and has tremendous potential in maritime target surveillance, which needs simultaneously wide coverage and high temporal resolution. The Chinese GF-4 satellite, launched in 2015, is the first array staring-imaging optical remote sensing satellite and has the highest spatial resolution in GEO remote sensing satellites at present. The staring camera on the GF-4 satellite has the highest spatial resolution (50 m ground sample distance, GSD) in visible and near infrared (VNIR) band, the widest imaging coverage (400 km \(\times\) 400 km) and the highest temporal resolution (20 s) of any similar existing systems [1]. The spatial resolution of 50 m is much lower than the high resolution (\(\leq\)5 m) of remote sensing satellites in low Earth orbit (LEO), but it is good enough to track large ships in near-real time from space. The staring camera, almost like a video camera, has high responsiveness and high-revisit observation capabilities. It cannot only adjust to the observation area within a few minutes, but also features high-frequency continuous imaging of the same area [2]. These new features enable the GF-4 satellite to play a significant role in many applications, especially in marine surveillance, which can be used for ship traffic surveillance, coastal management, and military purposes [3]. Therefore, this paper presents a complete processing algorithm for ship tracking using GF-4 satellite sequential images. The consecutive image sequences of GF-4 satellites can be used to obtain ships' motion information,which can assist decision-making, guide high-resolution LEO satellites for further recognition and identification, and so on. The GEO remote sensing satellite has become a new powerful tool in maritime surveillance. Recently, automatic identification system (AIS) satellite constellations have been available for cooperative ships' surveillance. However, in piracy, terrorism, illegal weapons proliferation, irregular immigration, drug smuggling, illegal fisheries, and other activities, the AIS equipment of non-cooperative ships are intentionally turned off or camouflaged for deception. Besides, military ships always deliberately try to hide. Therefore, the GEO remote sensing satellite can help find ships which pose a threat, or are known to engage in illegal activities, especially for continuous observing. So far, target-tracking methods using image sequences are mostly designed for ground and aerial videos, which have narrow field of view (FOV), long observation time and the targets have richer features (e.g., shape, texture) with a high spatial resolution. While satellite images have wider FOV, lower spatial resolution and more targets in one scene compared to ground and aerial videos. Targets in satellite images have fewer pixels, less detail and lower discrimination. Targets motion parameters estimation using LEO remote sensing satellite images has been studied in recent years. Most high resolution optical remote sensing satellites carry panchromatic (PAN) and multispectral (MS) sensors that are in different positions. Then there is a slight time lag between the acquisitions of the PAN and MS images, which can be used to extract the moving information of targets. The single-pass imagery has been successfully used to extract motion information of vehicles and planes [4; 5; 6; 7; 8; 9; 10; 11], while the time lag is too small to detect low speed moving vessels. Motion parameters can also be estimated using along-track sequential or stereo satellite images, which are taken by agile remote sensing satellites such as WorldView-2 with multi-angular look capability [12; 13; 14; 15]. More recently, Skysat, Jilin-1 and Zhuhai-1 small satellite constellations, which can record short videos, have been successfully tested for tracking moving targets [16; 17; 18; 19].