Wavelets: a Versatile Tool for the High Frequency Surface Wave Radar

Widely used in image processing, wavelets seem to be a promising versatile tool for the high frequency surface wave radar (HFSWR). HFSWR is based on the ability of HF waves (3 MHz to 30 MHz) to propagate along the earth curvature. HFSWR can detect targets up to few hundred kilometers beyond the horizon. The two main applications of the HFSWR are the maritime surveillance of the exclusive economic zone (EEZ) and the remote sensing of the sea. Beside the classical noise which affects all radar signals, the detection capabilities of HFSWR suffer from two limitations: the sea clutter and the ionospheric clutter which are target masks. However sea clutter can be used to perform remote sensing of the sea. In this paper we are studying how wavelets may contribute to the improvement of radar signal processing. We consider general de-noising feature for radar signals, we carry out a wavelet-based improvement of remote sensing of oceanographic parameters and we show the first results of a wavelet-based processing for ionospheric clutter mitigation.