Synthesis of Measurement Filtering Algorithms in Navigation Systems of Unmanned Aircraft
DOI:
https://doi.org/10.20535/RADAP.2024.96.21-27Keywords:
filtering, smoothing, filter, polynomial, invariance, navigation, system, accuracy, error, noise, measurementAbstract
Unmanned aerial vehicles (UAVs) are one of the main areas of development of world aviation technology. The wide application of UAVs of various classes in both military and civilian spheres requires the development and production of high-precision on-board navigation systems of low cost, weight and dimensions. When designing navigation systems of unmanned aerial vehicles, it is assumed to use information from many sensors and correction tools, which allows to significantly increase the accuracy of the systems being developed.
To process navigational information in such systems, stochastic filtering algorithms, often the Kalman filter, and various modifications of it, which allow taking into account the nonlinear nature of the problem, are used.
Existing filtering algorithms are characterized by high computational complexity, and engineers face the problem of their practical implementation through an abstract form. That is why the work describes the method of structural synthesis of recurrent algorithms of polynomial filtering of measurements in navigation systems of unmanned aerial vehicles.
The proposed approach allows synthesizing effective polynomial filtering algorithms. At the synthesis stage, the properties of the filters are formed in terms of noise smoothing and dynamic error exclusion, and the conditions under which the digital filter will be stable are determined. The work presents an example of the synthesis of a filtering algorithm, the workability and efficiency of which is confirmed by the results of mathematical modeling.
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