Wu Jianxin

Improved accuracy of estimated covariance matrix with a novel approach based on STAP

The performance of space-time adaptive processing (STAP) will suffer severe degradation when the training data is contaminated by certain part of potential desired signal component, especially in the condition of the power of the target-like signal spills over the range gate due to the effect of the pulse-compression. To overcome this problem, a novel target-like signal reconstruction method depending on the estimation of the amplitude and phase of the target-like signal from the receiving signal containing clutter and noise components is proposed. Consequently a set of purer signals is achieved as the training samples to estimate the clutter and noise covariance matrix of the cell under test (CUT) and the terrible target processing output of the conventional algorithm is modified, leading to a better performance of STAP. Theoretical analysis and simulation results proved the effectiveness of our suggested method.