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Abstract.To solve the problem of target detection in heavy sea clutter, we make simulation study on a subspace-based clutter suppression method to improve signal to clutter ratio in the predicted target location, and thus to improve the detection performance. With the compound Gaussian model of the sea clutter, we first estimate the statistics of sea clutter by Expectation-Maximization (EM) algorithm, then exploit a subspace-based approach to further mitigate sea clutter. With the algorithm, the computational complexity is effectively reduced. Nonetheless the algorithm exhibits good performance of clutter suppression. Numerical results show that the algorithm is effective in sea clutter suppression. Fig.1 The structure of clutter suppression system.

To meet the requirement of extracting sea surface current information by a single station, we present the new concept of High Frequency SAR (HF-SAR), and consider the feasibility of extracting sea surface current by HF-SAR. Firstly the implementation aspects are described, then system model and velocity estimation algorithm are designed, and finally simulation model to extract surface current is implemented on a single resolution cell. Additive complex Gaussian noise is included in the model of SAR echo, and also an iterative approach is adopted to estimate the parameters of chirp signals. Simulation results show that by estimating the phase parameters from azimuth echoes, the velocity estimates of surface current are obtained, and the precision is enough to meet the requirements. It indicates that HF-SAR is theoretically feasible to be used in sea surface current extraction.

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