Detection performance analysis of recurrence quantification analysis measures for low observable target within sea clutter under different sea conditions

Abstract

An approach based on recurrence quantification analysis (RQA) measures is proposed to detect the low observable target within sea clutter in this study. Based on the criterion named the fixed amount of nearest neighbours, recurrence plots (RPs) are constructed. RQA measures are used to describe the line structures of the RPs. According to the differences between the RQA measures of sea clutter with and without a target, the low observable target within sea clutter can be detected. Four sea clutter datasets under different sea conditions in the IPIX OHGR database are selected to analyse the target detection performance of RQA measures. Compared with the multifractal correlation spectrum approach and the cell average constant false alarm rate detector, the author's approach can achieve a higher detection probability. Furthermore, the authors analyse the receiver operating characteristic curves of RQA measures in all of polarisations under different sea conditions. The experimental results show that the horizontal–horizontal polarisation dataset and one of the horizontal–vertical and vertical–horizontal polarisation datasets should be selected for the target detection, and the significant wave height has a greater influence on the target detection performance than the wind speed does.