Numerical simulations have become essential in the manufacturing of sheet metal parts, requiring accurate calibration of constitutive models to define material behaviour. Advances in optical methods now enable the measurement of various strain states through full-field measurements and heterogeneous test setups. Combining this data with inverse calibration techniques provides a reliable approach to model calibration, though its success depends on factors like the test configuration, constitutive models, and identification strategy used [1]. This study introduces a new mechanical test, inspired by the Arcan test, which induces strain path changes without unloading the specimen. The method aligns with the goals of Material Testing 2.0 [1], capturing multiple strain states in a single experiment and increasing data richness. Numerical simulations of the test were analysed for heterogeneity and compared with the traditional Arcan test. Material parameters for dual-phase steel were identified using data from both tests, allowing for a direct comparison. The results highlight how advanced test configurations can improve the accuracy and efficiency of material model calibration. Further improvements could be achieved by using more complex specimen geometries.