Impact of intensity integration time distribution on the measurement precision of Mueller polarimetry. (July 2019)

• Record Type: Journal Article
• Authors: Li, Xiaobo; Hu, Haofeng; Wu, Lan; Yu, Yin; Liu, Tiegen
• Is Part Of: Journal of quantitative spectroscopy & radiative transfer. Volume 231(2019)
• Page Start: 22
• Page End: 27
• Publication Date: 2019-07
• Subjects: Polarization -- Mueller polarimetry -- Measurement precision -- Integration time -- Estimation variance; Spectrum analysis -- Periodicals; Radiation -- Periodicals; Analyse spectrale -- Périodiques; Rayonnement -- Périodiques; Radiation; Spectrum analysis; Periodicals; 543.0858
• DOI: 10.1016/j.jqsrt.2019.04.021
• Languages: English
• ISSNs: 0022-4073

Abstract

Highlights: This article proposes a modified model of Mueller polarimetry with considering the integration time distribution for intensity measurement. The relations between measurement error, instrument matrix and integration time distribution are presented for both complete Mueller polarimetry and some common incomplete Mueller polarimetry. We demonstrate that the existing minimal estimation variance, and thus the upper bound of measurement precision cannot be broken by optimizing intensity integration time distribution. Abstract: Mueller polarimetry is an important technology to characterize the physical property of materials (such as thin films and scattering particles etc.). Therefore, the high measurement precision is significant for various applications. In this paper, a modified model considering integration time of intensity measurement is proposed to verify the impact of intensity integration time distribution on the measurement precision of Mueller polarimetry. In the presence of additive Gaussian noise, the optimal integration time distribution, which is determined by instrument matrix, that minimizes the noise propagation (and thus estimation variance) is also proposed for both complete Mueller matrix polarimetry and some common partial (or incomplete) Mueller matrix polarimetry. Furthermore, we found that the estimation variance can be further reduced by optimizing the integration time distribution for some given instrument matrices. However, we also verify that, for the first time to our knowledge, the existing minimal estimation variance, and thus the upper bound of measurement precision cannot be broken by optimizing intensity integration time distribution.