Target Detection in Sea-Clutter Using Stationary Wavelet Transforms

Small target detection in the maritime environment remains a challenging problem. Maritime radars traditionally use non-coherent processing methods due to the time-varying and range-varying nature of the Doppler spectra. However, the radar backscatter may contain sea-spikes, which can last for seconds and resemble targets. This paper presents an application of stationary wavelet transforms (SWT) to improve target detection in medium grazing angle X-band sea-clutter. Since different components (sub-bands) of the SWT decomposition reveal different spectral characteristics of the returned signal, a method of selecting the appropriate sub-band is presented using an entropy-based metric. A Monte Carlo simulation using a cell averaging constant false alarm rate detector is then used to demonstrate the improvement of the SWT scheme against unfiltered data.