A complex optical system used in polarization lidars often modifies the input polarization of the return signal so that it may significantly impact depolarization estimates and introduce errors to polarization lidar measurements. In most cases, retardation, depolarization, and misalignment of the system exist at the same time and interact with each other. Polarization effects of the system cannot be represented by a simple correction coefficient, so they cannot be removed using a traditional calibration method. Detailed analysis and correction technologies were provided to remove systematic biases in estimating depolarization values from a polarization lidar owing to multiple optical components. The Mueller matrices from an emitter to a receiver were calculated, and the expression for an aerosol depolarization parameter including system polarization effects was derived and obtained. In addition, the correction algorithm based on the Mueller matrix was introduced and provided. A polarization lidar was established, and the polarization characteristics of its optical components were measured with a laboratory ellipsometer; then, the Mueller matrix of the receiver was calculated and obtained. Lidar observations were performed, and our correction algorithm was applied to lidar field data. The results show that the correction method can significantly remove systematic polarization effects.
Usually, traditional insulation materials have a constant thermal resistance value that cannot change within the ambient temperature and will decrease as ambient humidity or external stress increases. Humans heavily rely on heating, ventilation, and air conditioning (HVAC) systems to meet the thermal comfort requirements of their bodies, giving rise to energy waste and global warming. As an infinitely available natural resource, air is one of the most efficient thermal retaining substances known to science. Inspired by soft pneumatic robotics, we propose an architecture for air-driven thermoregulation fabrics called soft robotic fabrics (SRF). By changing the thickness of trapped air layer in fabric system through SRF, wearers could modify garments’ thermal insulation performance. A fabrication method is introduced to rapidly manufacture low-cost pneumatic structures using various types of construction and dimensions. With excellent ductility, elasticity, and compression resistance, the thickness of SRF increases by 12 times or more after inflation, and the fabric even can lift an object 270 times heavier than its weight. The excellent deformability can effectively increase stable air layer between clothing and skin. Based on the Predicted Mean Vote–Predicted Percentage of Dissatisfied model, the thermoregulation capability of SRF helps HVAC expand the temperature setpoint range by 3–8 times when compared with traditional fabrics, and has far-reaching significance in saving energy.
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