Abstract
Space-time adaptive processing (STAP) for airborne radar with co-prime arrays is shown to have excellent superiority compared to traditional STAP with uniform linear array radar. However, high arithmetic computational complexity and large amount of training data are required in this approach. This motivates the authors to present a new approach which is relatively low computational load and fast convergence with satisfactory performance. Specifically, a reduced-dimension transformation in Doppler domain is incorporated into the existing approach. The reduced-dimension interference covariance matrix and target steering vector are then achieved by performing the reduced-dimension process, and hence two reduced-dimension STAP filters are designed using the derived interference covariance matrix and target-steering vector. Numerical simulations are carried out to reveal the superiority of the proposed approach.
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