Multispectral camouflage and radiative cooling using dynamically tunable metasurface.

With the increasing demand for privacy, multispectral camouflage devices that utilize metasurface designs in combination with mature detection technologies have become effective. However, these early designs face challenges in realizing multispectral camouflage with a single metasurface and restricted modes. Therefore, this paper proposes a dynamically tunable metasurface. The metasurface consists of gold (Au), antimony selenide (Sb2Se3), and aluminum (Al), which enables radiative cooling, light detection and ranging (LiDAR) and infrared camouflage. In the amorphous phase of Sb2Se3, the thermal radiation reduction rate in the mid wave infrared range (MWIR) is up to 98.2%. The echo signal reduction rate for the 1064 nm LiDAR can reach 96.3%. In the crystalline phase of Sb2Se3, the highest cooling power is 65.5 Wm-2. Hence the metasurface can reduce the surface temperature and achieve efficient infrared camouflage. This metasurface design provides a new strategy for making devices compatible with multispectral camouflage and radiative cooling.

LiDAR Echo Gaussian Decomposition Algorithm for FPGA Implementation.

As the existing processing algorithms for LiDAR echo decomposition are time-consuming, this paper proposes an FPGA-based improved Gaussian full-waveform decomposition method. The proposed FPGA architecture consists of three modules: (i) a pre-processing module, which is used to pipeline data reading and Gaussian filtering, (ii) the inflection point coordinate solution module, applied to the second-order differential operation and to calculate inflection point coordinates, and (iii) the Gaussian component parameter solution and echo component positioning module, which is utilized to calculate the Gaussian component and echo time parameters. Finally, two LiDAR datasets, covering the Congo and Antarctic regions, are used to verify the accuracy and speed of the proposed method. The experimental results show that (i) the accuracy of the FPGA-based processing is equivalent to that of PC-based processing, and (ii) the processing speed of the FPGA-based processing is 292 times faster than that of PC-based processing.