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In this paper, a novel approach for direct data domain space time adaptive processing (STAP) is presented. As already described in past literature, direct data domain STAP (also known as deterministic STAP) has several advantages compared to traditional stochastic STAP. In particular, being implicitly a single snapshot interference cancellation technique, deterministic STAP generally outperforms stochastic STAP in fast varying interference scenarios. On the other hand, in its classical derivation, target detection performances of deterministic STAP are severely deteriorated in case of uncertainty in the knowledge of exact target parameters as direction of arrival (DOA) and Doppler frequency. To overcome this problem, we propose a robust implementation of deterministic STAP in order to take into account a possible mismatch between the nominal and the actual target parameters. The proposed approach reformulates the deterministic STAP problem in the context of convex problem optimization. A detailed analysis of the maximum acceptable target parameters error is conducted, which ensures the existence of a numerical solution for the convex problem optimization. The proposed robust deterministic approach is defined for both the one dimensional (spatial-only) and the two dimensional (space-time) case. The effectiveness of the proposed approach is shown both in simulated scenarios and by direct application to real data taken from the experimental multichannel radar system PAMIR developed at Fraunhofer FHR.