Polarimetric agile radar is able to measure all elements of the polarization-dependent backscattering matrix (BSM) simultaneously. Polarimetric calibration is an important issue to determine the BSM accurately. This paper focuses mainly on the internal and semi-external calibration of the dual-channel polarimetric agile radar system. The paper presents a novel approach based on very up to date methods used for cross-validation between simulations and measurements. Error models of all parts of the radar system will be derived from the approach and implemented in the radar system calibration. After calibration, the good matching performance for relative measurement between two channels demonstrates the validity of the here-proposed calibration approach.@en

Polarimetric agile radar is able to measure all elements of the polarization-dependent backscattering matrix (BSM) simultaneously. Polarimetric calibration is an important issue to determine the BSM accurately. This paper focuses mainly on the internal and semi-external calibration of the dual-channel polarimetric agile radar system. The paper presents a novel approach based on very up to date methods used for cross-validation between simulations and measurements. Error models of all parts of the radar system will be derived from the approach and implemented in the radar system calibration. After calibration, the good matching performance for relative measurement between two channels demonstrates the validity of the here-proposed calibration approach.@en

In this paper we study a general energy minimization problem for mixed-criticality systems on multi-cores, considering different system operation modes, and static & dynamic energy consumption. While making global scheduling decisions, trade-offs in energy consumption between different modes and also between static and dynamic energy consumption are required. Thus, such a problem is challenging. To this end, we first develop an optimal solution analytically for unicore and a corresponding low-complexity heuristic. Leveraging this, we further propose energy-aware mapping techniques and explore energy savings for multi-cores. To the best of our knowledge, we are the first to investigate mixed-criticality energy minimization in such a general setting. The effectiveness of our approaches in energy reduction is demonstrated through both extensive simulations and a realistic industrial application.@en