Stringent magnetostatic cleanliness programs are required for interplanetary scientific spacecraft like Ulysses, Cluster,Double Star, Cassini, Rosetta many others, which carry sensitive magnetometers operating in a low interplanetary field environment. Due to the strong Earth field and the limited precision of coil facilities it is impossible to verify the stringent magnetic cleanliness specification (typically 0.1-1 nT) by direct measurements at the specification point. The paper describes the use of Multiple Dipole Models which generates precise far-field estimates. The model parameters of the so-called MDMs are identified on the basis of near-field measurements. The method, developed by K. Mehlem in the early eighties, is implemented in the GAMAG software. The paper mentions some historical aspects and describes in more detail the NLP solver used, as well as some inherent identification problems which are due to data sparsity and to parameter-constraints. The characteristics of the software are presented, in particular the efficient combination of deterministic and stochastic solver strategies, the statistical refinement of far-field estimates, the capabilities to optimize compensation MDMs (magnets or coils) for multiple far-field points, and finally the ease of use.
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