Abstract
Bidirectional Reflectance Distribution Function (BRDF) at variable temperature is important in many applications such as thermal imaging and target detection. However, ensuring long-term stable high temperature control is complex and energy consuming, making online measurements essential. Existing BRDF systems are mainly designed for room temperature measurements, and the widely used quadrature demodulator requires a large amount of stored measurement data and complicate post-processing calculations. In this paper, the Kalman-based demodulator was modified by adding a forgetting factor to improve the demodulation speed and flexibility. This demodulator was implemented on FPGA in both numerical simulations and experiments. The detection of BRDF was demodulated online, reducing measurement time and resource consumption by half compared to the quadrature demodulator. The proposed demodulator can be utilized for further analysis of high-temperature BRDF characteristics of material surfaces.
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