Invariant Polarization Signatures for Recognition of Hydrometeors by Airborne Weather Radars

@InProceedings{10.1007/978-3-031-36805-9_14, author="Popov, Anatoliy and Tserne, Eduard and Volosyuk, Valerii and Zhyla, Simeon and Pavlikov, Vladimir and Ruzhentsev, Nikolay and Dergachov, Kostiantyn and Havrylenko, Olena and Shmatko, Oleksandr and Averyanova, Yuliya and Ostroumov, Ivan and Kuzmenko, Nataliia and Sushchenko, Olga and Zaliskyi, Maksym and Solomentsev, Oleksandr and Kuznetsov, Borys and Nikitina, Tatyana", editor="Gervasi, Osvaldo and Murgante, Beniamino and Taniar, David and Apduhan, Bernady O. and Braga, Ana Cristina and Garau, Chiara and Stratigea, Anastasia", title="Invariant Polarization Signatures for Recognition of Hydrometeors by Airborne Weather Radars", booktitle="Computational Science and Its Applications -- ICCSA 2023", year="2023", publisher="Springer Nature Switzerland", address="Cham", pages="201--217", abstract="Hydrometeors, such as thunderclouds, hail, and snow, pose a threat to the safety of civil aviation flights. For their timely detection, airborne weather radars with dual polarization of radiation, two-channel reception of reflected signals, and signal processing by artificial intelligence methods are used, which makes it possible to distinguish signatures for the detection and recognition of dangerous hydrometeors for flights. The dependence of the characteristics of the reflected signal on a variety of microphysical and macrophysical parameters requires an expansion of the signature space to improve the reliability of detection. This article proposes invariant polarization signatures of hydrometeors, which are defined on the basis of the coherent decomposition of eigenvalues and eigenvectors of the polarization backscattering matrix. Based on the data of experimental studies, it is shown that the polarization parameters of the radar targets eigenbasis allow distinguishing the degree of ordering of hydrometeor particles (a characteristic feature of thunderstorm core in clouds) and the parameters of the invariant polarization transfer functions of hydrometeors make it possible to estimate the phase state of the hydrometeor, the presence of ice particles in it, hail, etc. even when the radar observes some mixture of hydrometeors of various types. The obtained results will improve the efficiency of the application of artificial intelligence methods in airborne meteorological radars.", isbn="978-3-031-36805-9" }