Abstract
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.
Highlights
High Frequency Surface Wave Radar (HFSWR) exploits the surface wave mode of vertical polarization electromagnetic wave propagating over the sea water to detect ships and aircrafts at distances beyond the line of sight
To counter the nonhomogeneous ionospheric clutter background of HFSWR, this paper proposes a feature analytical algorithm based on the Angle-Doppler Joint Eigenvector to analyze the range correlation of the nonhomogeneous ionospheric clutter
It turns out that the range correlation coefficient is irregular in its variation
Summary
HFSWR exploits the surface wave mode of vertical polarization electromagnetic wave propagating over the sea water to detect ships and aircrafts at distances beyond the line of sight. In HFSWR systems, long coherent integration time is necessary for better detection performance and higher Doppler resolution During this process, the state of the ionosphere is changing rapidly and irregularly, which leads to an obvious problem that the ionospheric clutter can cover a few Doppler shift units after the coherent integration. Joint domain localized (JDL) is a classical statistical STAP algorithm broadly used in airborne radar [15] It features preferable low computational cost and high performance in homogeneous clutter suppression. Direct data domain (D3), hybrid, and PAMF are classical STAP algorithms for nonhomogeneous clutter in airborne radar systems. These algorithms suffer from high computational cost and poor real-time performance in HFSWR due to the long coherent integration time (CIT) and large space-time dimension. The superiority of the improved-JDL algorithm is demonstrated via simulation based on practically measured data
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