Robust Target Detection Within Sea Clutter Based on Graphs
Kun Yan, Yu Bai, Hsiao‐Chun Wu, Xiangli Zhang · IEEE Transactions on Geoscience and Remote Sensing · 2019
In this paper, a novel robust graph-based adequate and concise information representation paradigm is explored. This new signal representation framework can provide a promising alternative for manifesting the essential structure of random signals. A typical application, namely, target detection within sea clutter, can thus be carried out using our proposed new graph-based signal characterization. According to Monte Carlo simulation results, the proposed graph-based signal (target) detection method leads to the outstanding performance, compared to other existing techniques, especially when the signal-to-noise ratio is rather small (0-6 dB). This new graph-based target detector can be expected to be the future backbone technique for identifying and tracking marine vessels using high-resolution radars.