Robust STAP Algorithm under the Steering Vector Uncertainty Set

For solving the problem of optimum space-time adaptive processing (STAP) under the steering vector mismatch, a robust STAP algorithm is proposed based on the concept of robust Capon beamforming. The model of the steering vector error is established, describing the uncertainty of the desired steering vector. And a new optimization criterion is formed, by which the robust weight vector is acquired. Eventually experimental results and analysis are given with simulation signals. It is verified that the presented method is insensitive to the steering vector error and has a bigger improvement factor.

Robust Adaptive Beamforming Imaging Approach for Stepped-Frequency through-the-Wall Radar

A robust Capon adaptive beamforming imaging method was proposed for stepped-frequency through-the-wall radar. According to the ideal of robust Capon beamforming (RCB) under the steering vector uncertainty set, Capon optimal weight vector in frequcency domain is obtained by accurately estimating Compensation function vector. Then signal energy is estimated by freqency weighting, and coherence factor (CF) weighting is applied to suppress sidelobe level. Therefore, this method not only achieves higher resolution and much better interference suppression capabilities, but also improves imaging contrast.