Adaptive temporal processing for equatorial spread Doppler clutter suppression

The detection performance of skywave HF over-the-horizon radars is fundamentally limited by ionospheric motion which causes spreading of surface clutter returns in Doppler space. This work presents an adaptive temporal processing approach for suppressing range-azimuth coincident spread Doppler clutter (SDC). Our method exploits the spatial correlation of the ionospheric aberration, which causes clutter covariance matrix components averaged over directions aligned with the Earth's magnetic field to be a low rank. For radars looking north-south, this property in turn facilitates suppression of SDC in the target range bin by estimating the clutter covariance matrix from neighboring range bins. Because the sample support for covariance estimation along field-aligned directions is limited, an optimal constrained ML estimate of the covariance matrix was used for effective clutter suppression. Initial processing on experimental spread Doppler clutter data with injection of a simulated target illustrates that this approach can provide a target-to-clutter ratio improvement greater than 15 dB.