Ship Detection and Direction Finding Based on Time-Frequency Analysis for Compact HF Radar

Abstract

Ship detection at the sea surface is important for improving human marine activities. Most existing ship detection methods for high-frequency surface wave radar (HFSWR) are based on peak and constant false alarm rate (CFAR) detection and require a coherent integration time (CIT) of several minutes. However, in such a long period, the target may not be stationary. To account for the nonstationary property, a time-frequency analysis (TFA)-based ship detection and direction finding (DF) method is proposed for HFSWR. Target ridges on the TF representation (TFR) of the echo data are detected first. Next, array snapshots are formed by sampling the extracted ridges and are used to estimate the direction of arrival (DOA). The processing results of the radar data collected at Dongshan, Fujian Province, China, show that the proposed method outperforms the CFAR method with both increased detection rates and decreased DF errors, especially under relatively low signal-to-noise ratio (SNR) scenarios.