The article describes the methodology for the determination of ambient temperature for thermovision measurements. The adopted methodology consists in the use of the technical blackbody model. Determining the value of the ambient temperature parameter makes it possible to enhance the accuracy of temperature measurement of objects exposed to strong irradiation using a thermovision camera.

Outdoor remote temperature measurements in the infrared range can be very inaccurate because of the influence of solar radiation reflected from a measured object. In case of strong directional reflection towards a measuring device, the error rate can easily reach hundreds per cent as the reflected signal adds to the thermal emission of an object. As a result, the measured temperature is much higher than the real one. Error rate depends mainly on the emissivity of an object and intensity of solar radiation. The position of the measuring device with reference to an object and the Sun is also important. The method of compensation of such undesirable influence of solar radiation will be presented. It is based on simultaneous measurements in two different spectral bands, shor-twavelength and long-wavelength ones. The temperature of an object is derived from long-wavelength data only, whereas the short-wavelength band, the corrective one, is used to estimate the solar radiation level. Both bands were selected to achieve proportional changes of the output signal due to solar radiation. Knowing the relation between emissivity and solar radiation levels in both spectral bands, it is possible to reduce the measurement error several times.

The article presents a new discretization method of a continuous-time linear model of sensor dynamics. It can be useful to reduce measuring errors related to the inertia of the sensor. For example it is important in the measurement of rapid processes as temperature changes in combustion chambers, or for shortening the time needed to establish the sensor readings in a transition state. There is assumed that sensor dynamics can be approximated by linear differential equation or transfer function. The searched coefficients of equivalent difference equation or discrete transfer function are obtained from Taylor expansion of a sensor output signal and then on the solution of the linear set of equations. The method does not require decomposition of sensor transfer function for zeros and poles and can be applied to the case of transfer function with zeros equal to zero. The method was used to compensate the dynamics of sensor measuring fast signals. The Bode characteristics of a compensator were compared with others derived using classical methods of discretization of linear models. Additionally, signals in time were presented to show the dynamic error before and after compensation.