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Identification of crystallographic slip in metals and alloys is crucial to understand and improve their mechanical behavior. Recently, a novel slip system identification framework, termed SSLIP (for Slip System-based Local Identification of Plasticity), was introduced to leap from conventional trace-based identification to automated, point-by-point identification that exploits the full deformation kinematics. Using microstructure-correlated deformation data, SSLIP matches the measured in-plane displacement gradient tensor to the kinematics of the optimal combination of multiple slip system activities, at each DIC datapoint. SSLIP was applied and demonstrated to be successful on virtual and experimental case studies of FCC and BCC metals. However, for more advanced and anisotropic HCP crystal structures the complete identification of all slip systems was found to be more challenging, posing limitations on automation and flexibility. Here, we propose a significant extension to the SSLIP framework with the aim of automated slip system identification of HCP. The main extensions of the SSLIP method, hereinafter referred to as the +SSLIP method, include (i) a pre-selection of slip systems using a Radon transform, (ii) robustness to measured rigid body rotation by simultaneous identification of the local elastic rotation field, (iii) identification of the two best matching slip systems for each data point, and (iv) a procedure to deal with slip systems with in-plane displacement gradient tensors that cannot be discriminated, yielding the full slip system activity maps with all slip systems for each grain. The resulting objective identification method does not rely on, e.g., the Schmid factor to select which slip system is active at each point. We show how slip systems from multiple slip families are successfully identified on virtual and real experiments on a Zn polycrystalline coating.