Synthesis of an optimal digital filter of a compensation radiometer for radiometric correlation-extreme navigation systems of unmanned aerial vehicles
DOI:
https://doi.org/10.15587/1729-4061.2021.230176Keywords:
unmanned aerial vehicles, correlation-extreme navigation systems, digital filter, weight coefficientsAbstract
The expediency of using a compensation radiometer (CR) with periodic absolute calibration as a sensor for preprocessing the information of correlation-extreme navigation systems (CENS) of unmanned aerial vehicles (UAV) was shown. This is determined by the possibility of obtaining and using the estimates of gain fluctuations obtained in previous frames which will provide an increase in the radiometer sensitivity. In addition, due to the accumulation of information, an increase in accuracy of measurement of the elements of the current image formed by the CENS will be provided.
The algorithm of processing the obtained calibration estimates during linear processing corresponds to a certain digital filter (DF). By defining a set of the DF weight coefficients, it is possible to improve the CR fluctuation sensitivity by reducing the gain fluctuations. Up to 1.8-time gain in sensitivity can be reached for typical frequency and time parameters of the compensation radiometer of UAV CENS.
The problem of synthesis of a digital filter was set. A solution to the problem of synthesizing an optimal digital filter was proposed. Its use in a CR will improve the fluctuation sensitivity. In its turn, this will make it possible to improve the quality of a current image generated by the system when siting by means of sighting surfaces with low-contrast objects taking into account fluctuations in radio-brightness temperature.
It was found that the gain in sensitivity when using the optimal digital filter increases with an increase in the operating period of the radiometer and an increase in the digital filter order.
Improvement of fluctuation sensitivity of the CENS data preprocessing system is important for UAV location in low-contrast areas
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Copyright (c) 2021 Наталія Сергіївна Єрьоміна, Сергій Валерійович Петров, Максим Олександрович Волк, Олена Анатоліївна Дакі, Володимир Миколайович Чередник, Ірина Анатоліївна Зінченко, Ігор Вікторович Черних, Олексій Вікторович Алексеєнко, Сергій Анатолійович Микусь, Володимир Данилович Фурдик
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