Sea-Surface Small Target Detection Based on Four Features Extracted by FAST Algorithm

Abstract

On account of current algorithm and parameter design difficulties and low detection accuracy in feature extractions of small target detections in sea clutter environment, this paper proposes a correspondingly improved four feature extraction method by FAST. After the short-time Fourier transform is applied, a time–frequency distribution spectrogram of original data is generated. Candidate feature points (CFP) are first extracted by FAST algorithm, and then a four-feature extraction is implemented with FAST and DBSCAN combined. The feature distinction is enhanced through a feature optimization. Upon the construction of the four-dimensional feature vectors, XGBoost classifier algorithm classifies and detects these feature vectors. The genetic algorithm optimizes the hyperparameters in XGBoost and updates the decision threshold in real time to control the detection method’s false alarm rate. The IPIX dataset is employed for experimental verification. Verification results confirm that this proposed detection method has better performance than several other currently used detection methods. The detection performance is improved by 7% and 13.8% when observation time is set at 0.512 s and 1.024 s, respectively.

Sea-Surface Small Target Detection Based on Improved Markov Transition Fields

“…Relevant studies are shown in Table 1. Difficulties in feature extraction [7] As deep learning research continues to advance, convolutional neural networks [8,9] have been used to classify sea clutter and noise. Through convolutional neural networks and feature perception technologies, researchers have proposed various image-based encoding methods to enhance the accuracy and generalization capability of target detection, as shown in Table 2.…”

Nearshore Depth Estimation Using Fine-Resolution Remote Sensing of Ocean Surface Waves

“…Existing applications of the wave bathymetry method through optical remote sensing (WBM-ORS) wave depth measurement method have shown that both the Fast Fourier Transform (FFT) and SPM methods yield accurate depth measurement through wavelength inversion [40,50]. However, the FFT method still has limitations in certain scenarios [51,52]. Shen et al conducted simulation research and found that the FFT method requires a specific image resolution and subimage size, with the subimage length being 4-8 times the wavelength [53].…”