A Novel Approach of Extracting Ship Scatterer's 3-DOF Micromotion Features Under Long Accumulation Time

Abstract

The rolling, pitching, and yawing motion of the vessel produces a micro-Doppler signature in the radar echoes. Ship scatterers’ three-degree-of-freedom (3-DOF) micromotion features contain information on the ship geometric structure and motion parameters. Therefore, it is essential to extract the 3-DOF micromotion features of ship scatterers with high accuracy. Because existing approaches to extracting 3-DOF micromotion features of ship scatterers under long accumulation time have the disadvantage of low accuracy, we propose a high-precision algorithm based on linear micro-Doppler trajectory tracking after performing a generalized S-transform and ridge extraction to coarsely analyze the time-frequency trajectory corresponding to the ship's echo. To improve the extraction accuracy of 3-DOF micromotion features of ship scatterers, long time is divided into many short time segments. The motivation for time segmentation is that the instantaneous Doppler frequency of a scatterer caused by a ship's rotation is verified to behave approximately as a linear frequency modulation signal over a short period. The Doppler centroids and frequency modulation rates of scatterers during a short time segment in a given range bin can be easily coarsely estimated from ridge extraction results. The instantaneous Doppler frequency trajectories of the same scatterer in adjacent short time segments are correlated and filtered by using the nearest neighbor algorithm and the extended Kalman filtering algorithm to achieve high estimation accuracy. The results of the performed simulation and processing of real radar data verify the accuracy of the proposed algorithm is higher than those of the current commonly used algorithms.

Keywords

• Linear micro-Doppler trajectory tracking
• long accumulation time
• three-degree-of-freedom (3-DOF) micromotion feature
• time segmentation