The total solar irradiance (TSI) refers to the sum of the solar electromagnetic radiation energy of all wavebands reaching the top of the earth's atmosphere per unit area in unit time at the average distance between the sun and the earth (Biktash & Lilia, 2017). Although the solar radiation energy received by the earth is only one in two billion of the total radiation energy from the sun to the space, but it is the main energy source of the earth's atmospheric movement, it is the most important energy source of the earth's atmospheric movement and an important external driving factor of global climate change (Haigh, 2007;Kren, 2015;Solanki et al., 2013). Before Hickey-Frieden cavity radiator (HF) was used to observe the solar radiation in October 1978, TSI was regarded as a constant due to the low accuracy of ground observation equipment, so it was called "solar constant." Since HF was launched, TSI has been continuously observed by several radiometers. Due to the high accuracy of these space radiometers, it is recognized that the solar radiation varies from several minutes to several decades (Kopp, 2016). TSI produces the earth's radiation environment and affects the earth's temperature and atmosphere, even a small change in TSI will have a profound impact on the earth's climate (

In the literature, the fading factor was constructed to overcome the shortage of model uncertainties in the Kalman filter. However, the a priori covariance matrix might be inflated abnormally by the fading factor once the measurement is unreliable. Thus, the fading factor may become invalid, and this problem is rarely discussed and tested. In this paper, squares of the Mahalanobis distance are introduced as the judging index, and the fading factor or the covariance inflation factor is adopted conditionally according to the hypothesis testing result. Therefore, an adaptive filtering scheme based on the Mahalanobis distance is put forward for the systems with model uncertainties. The proposed algorithm is implemented with the actual data collected by the integration of the global navigation satellite system (GNSS) and the inertial navigation system and INS (inertial navigation system) integrated systems (INS). For the systems with model uncertainties, experimental results demonstrate that the influences of both the outlying measurements and model errors are controlled effectively with the proposed scheme.

Precision and accuracy estimation is an important index used to reflect the measurement performance and quality of a measurement system. To reveal the significance and connotations of the precision and accuracy estimation index of a close-range photogrammetry system, several common precision and accuracy estimation methods are proposed. They are explained from a theoretical perspective, and the mechanism of the internal coincidence precision estimation and the external coincidence accuracy estimation are deduced, respectively. Through detailed experimental design and testing, the validity and reliability of the proposed precision and accuracy estimation methods are verified, which provides strong evidence for the quality control, optimization and evaluation of the measurement results from a close-range photogrammetry system. At the same time, it has significance for the further development of precision and accuracy estimation analysis of close-range photogrammetry systems.

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