Abstract
The geostationary remote sensing satellite has the capability of wide scanning, persistent observation and operational response, and has tremendous potential for maritime target surveillance. The GF-4 satellite is the first geostationary orbit (GEO) optical remote sensing satellite with medium resolution in China. In this paper, a novel ship-tracking method in GF-4 satellite sequential imagery is proposed. The algorithm has three stages. First, a local visual saliency map based on local peak signal-to-noise ratio (PSNR) is used to detect ships in a single frame of GF-4 satellite sequential images. Second, the accuracy positioning of each potential target is realized by a dynamic correction using the rational polynomial coefficients (RPCs) and automatic identification system (AIS) data of ships. Finally, an improved multiple hypotheses tracking (MHT) algorithm with amplitude information is used to track ships by further removing the false targets, and to estimate ships’ motion parameters. The algorithm has been tested using GF-4 sequential images and AIS data. The results of the experiment demonstrate that the algorithm achieves good tracking performance in GF-4 satellite sequential images and estimates the motion information of ships accurately.
Highlights
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 spatial resolution of 50 m is much lower than the high resolution (≤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
A ship-tracking algorithm applied to the GF-4 satellite is proposed, which is designed based on ship detection, position correction and ship-tracking three-step processing
Summary
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. It cannot only adjust to the observation area within a few minutes, and 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]. This paper presents a complete processing algorithm for ship tracking using GF-4 satellite sequential images
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