Abstract
The ability to determine the number and location of offshore platforms is of great significance for offshore oil spill monitoring and offshore oil and gas development. Considering the problem that the detection threshold parameters of the two-parameter constant false alarm rate (CFAR) algorithm require manual and repeated adjustment of the during the extraction of offshore platform targets, this paper proposes a two-parameter CFAR target detection method based on maximum entropy based on information entropy theory. First, a series of threshold parameters are obtained using the two-parameter CFAR algorithm for target detection. Then, according to the maximum entropy principle, the optimal threshold is estimated to obtain the target detection results of the possible offshore platform. Finally, the neighborhood analysis method is used to eliminate false alarm targets such as ships, and the final target of the offshore platform is obtained. In this study, we conducted offshore platform extraction experiments and an accuracy evaluation using data from the Pearl River Estuary Basin of the South China Sea. The results show that the proposed method for platform extraction achieves an accuracy rate of 97.5% and obtains the ideal offshore platform distribution information. Thus, the proposed method can objectively obtain the optimal target detection threshold parameters, greatly reduce the influence of subjective parameter setting on the extraction results during the target detection process and effectively extract offshore platform targets.
Highlights
Petroleum and natural gas resources are the economic lifeblood of national development and occupy an extremely important strategic position
The two-parameter constant false alarm rate (CFAR) target detection method based on maximum entropy proposed in this paper was applied to the distribution of offshore platforms in the Pearl River Estuary Basin of the South China Sea
We evaluated the results of offshore platform extraction using three indicators in our previous published paper: true positive (TP) rate, false negative (FN) rate and false positive (FP)
Summary
Petroleum and natural gas resources are the economic lifeblood of national development and occupy an extremely important strategic position. As offshore drilling technology has matured, the exploitation of offshore oil and gas resources has increased. As a primary type of equipment for offshore oil and gas resource development, the number and location of offshore platforms reflect a country’s oil and gas resource development intensity and capacity to some extent [1]. Information concerning the distribution of offshore platforms is of great significance in applications such as maintaining channel security and monitoring offshore oil spills [2]. Offshore platform distributions were obtained via field surveys, which were time-consuming and costly. Remote sensing images cover a wide area, making them convenient for providing information on large numbers of offshore platforms.
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