Array Error Calibration Method for Pre-Whitened Space-Time Adaptive Processing

Pre-whitened space-time adaptive processing (STAP) can obtain fast convergence rate and achieve better clutter suppression performance in heterogeneous clutter environment. However, pre-whitened STAP shows significantly performance degradation in the presence of array errors. To solve this problem, we propose a novel method based on clutter echo to calibrate the array errors online. Firstly, the array errors are represented as orientation-dependent gain-phase errors; Then, the main-lobe clutter in every direction will be used as calibration source, and the gain-phase errors in the corresponding direction can be estimated on the basis of the property that its covariance matrix of the array output does not preserve the Toeplitz structure due to the effect of the array errors. Finally, the estimates of the gain-phase errors are used to calibrate the prior covariance matrix and the assumed target steering vector. The simulation results verify the effectiveness of the proposed algorithm.