High Frequency Surface Wave Radar (HFSWR) can perform the functions of ocean environment monitoring, target detection, and target tracking over the horizon. However, its system's performance is always limited by the severe ionospheric clutter environment, especially by the nonhomogeneous component. The nonhomogeneous ionospheric clutter generally can cover a few Doppler shift units and a few angle units. Consequently, weak targets masked by the nonhomogeneous ionospheric clutter are difficult to be detected. In this paper, a novel algorithm based on angle-Doppler joint eigenvector which considers the angle-Doppler map of radar echoes is adopted to analyze the characteristics of the nonhomogeneous ionospheric clutter. Given the measured data set, we first investigate the correlation between the signal of interest (SOI) and the nonhomogeneous ionospheric clutter and then the correlation between the nonhomogeneous ionospheric clutters in different two ranges. Finally, a new strategy of training data selection is proposed to improve the joint domain localised (JDL) algorithm. Simulation results show that the improved-JDL algorithm is effective and the performance of weak target detection within nonhomogeneous ionospheric clutter is improved.
Distributed Target Detection Based on the Volume Cross-Correlation Function
