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Multistatic spaceborne SAR offers in addition to powerful Earth imaging and remote sensing the possibility to detect the presence of slowly moving objects due to the large baselines. In contrary to monostatic multi-subaperture systems with classical STAP processing the multi-satellite system overcomes the problem of blindness against certain directions of target motion. Moreover velocity and direction of target motion can be estimated with considerably higher accuracy when taking advantage of the geometry of the multistatic configuration. For this purpose non-classical algorithms have to be developed. Furthermore, the application of optimum detection schemes and the exact analysis of MTI performance are challenging tasks. Indeed the high system complexity and the huge amount of data to be analysed make the MTI processing exceedingly difficult. Therefore only sub-optimum methods can be implemented. In this paper we propose a sub-optimum approach for multistatic spaceborne moving target detection. First of all we define a signal model for both moving targets and clutter proceeding from an arbitrary multistatic configuration. Secondly, we present the sub-optimum statistical processing based on the exploitation of the covariance matrix describing the common statistical properties of the random vector composed of a selected number of resolution cells in the range-Doppler-space for all sensor channels. Then we analyse the MTI performance of representative multistatic configurations. Finally this method is applied to simulated data of multistatic satellite systems.