Abstract:

Space-time adaptive processing (STAP) for airborne radar combined with the monopulse technique can be used〖JP〗 for estimating the spatial and temporal parameters of moving targets. However, in nonhomogeneous environments, the clutter covariance matrix is difficult estimated accurately due to the amount of identically distributed training data is limited. As a result, the performance of optimum STAP and its modified versions dramatically decrease, especially those methods are failed. Additionally, in this case the effectively target detection and parameters estimation cannot be realized. A novel method is proposed for parameters adaptive estimation via no secondary data. This method calculates the covariance matrix by applying the amplitude and phase estimation (APES) filter in the primary data firstly. Then, by combining STAP technique with the monopulse theory, the ground clutter is suppressed and the estimation of angle and Doppler frequency is obtained. Simulation results show that the proposed method has the capability of adaptive clutter suppression and can achieve accurate parameter estimation performance compared with the conventional monopulse method. This method is outstanding in severe nonhomogeneous environments, because it does not need any secondary data.