This paper describes the results of the research fulfilled in TU-Delft by joint Ukrainian and Dutch team. It analyzes multi-instrument rain observations, using the instrument set, which includes W-band cloud radar, laser optical disdrometers, weather station, and microwave radiometer. New friendly interface software is developed, presented, and used as a tool for comparison and fusion of diverse sensors datasets. The results obtained demonstrate the synergy of multi-instrument measurements and corresponds to the overarching trends of big data analysis. The intricacies of combining data from various sources to enhance calibration and improve the accuracy of atmospheric studies is discussed. In particular, analysis of 94 GHz cloud radar calibration based on disdrometer measurements with application of additional multi-instrument measurements is performed.

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This paper is devoted to discussing peculiarities of W-band cloud radar calibration. After a brief overview of meteorological radar calibration methods for quantitative information retrieval, we focus on problems and their possible solutions with respect to mm-wave radar calibration. The experimental part of the research is based on multi-instrument measurements performed during several years in the Cabauw experimental meteorological site in the Netherlands. The accumulated data are used for comparison of 94 GHz radar rain measurements with non-radar droplet size distribution measurements, provided by laser disdrometers. Calculations are done taking into account data of other in situ meteorological measurements. A specialized MATLAB software tool for processing such complex data and radar calibration is developed and demonstrated.

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This article proposes a receiving device in which arbitrary input signals are subject to pre-detector processing for the subsequent implementation of the idea of compressing broadband modulated pulses with a matched filter to increase the signal-to-noise ratio and improve resolution. For this purpose, a model of a dispersive delay line is developed based on series-connected high-frequency time delay lines with taps in the form of bandpass filters, and analysis of this model is performed as a part of the radio receiving device with chirp signal compression. The article presents the mathematical description of the processes of formation and compression of chirp signals based on their matched filtering using the developed model and proposes the block diagram of a radio receiving device using the principle of compression of received signals. The proposed model can be implemented in devices for receiving unknown signals, in particular in passive radar. It also can be used for studying signal compression processes based on linear frequency modulation in traditional radar systems.

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This paper proposes generalized mathematical model of different passive interferences and develops an effective algorithm of digital signal processing for detection on the background of them. Models of interferences as random process of K-distribution is used with parametrization for the unwanted reflections from atmosphere, land, and sea. Robust algorithm for signal detection on the background of such interferences, in particular in case of non-gaussian distribution, is developed. Its effectiveness is researched and confirmed.

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This paper considers generalized coherent-polarimetric method of retrieving information about remote objects using electromagnetic waves. Both active and passive electronic systems as well as different objects under observation, operating frequency bands, and physical meaning (interpretation) of the frequency as spectral argument can be used. As an example, retrieving information about turbulence using microwave weather radar is considered.

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The generalized mathematical and computer model of clutter is developed. It is based on K-distribution and can be used for simulation of sea, atmospheric, and land clutter with different characteristics. Examples of model application for testing rank algorithm for clutter suppression are considered and analyzed.@en

A new model is proposed on how to account for the inertia of scatterers in radar-based turbulence intensity retrieval techniques. Rain drop inertial parameters are derived from fundamental physical laws, which are gravity, the buoyancy force, and the drag force. The inertial distance is introduced, which is a typical distance at which a particle obtains the same wind velocity as its surroundings throughout its trajectory. For the measurement of turbulence intensity, either the Doppler spectral width or the variance of Doppler mean velocities is used. The relative scales of the inertial distance and the radar resolution volume determine whether the variance of velocities is increased or decreased for the same turbulence intensity. A decrease can be attributed to the effect that inertial particles are less responsive to the variations of wind velocities. An increase can be attributed to inertial particles that have wind velocities corresponding to an average of wind velocities over their backward trajectories, which extend outside the radar resolution volume. Simulations are done for the calculation of measured radar velocity variance, given a 3-D homogeneous isotropic turbulence field, which provides valuable insight in the correct tuning of parameters for the new model.@en

This paper considers new possibilities of turbulence intensity retrieval by using Doppler and Doppler-polarimetric radar sounding. Pecularities of microwave scattering on moving droplets of different size and shape underlie new methods that are introduced, discusssed, and checked by using radar data.@en

A model of Doppler-polarimetric radar signals due to rain is developed. It gives Doppler spectra at different combinations of linear polarization of transmitted and received waves. The spectral differential reflectivity and spectral linear depolarization ration and introduced. The model uses the rain microstructure and turbulence parameters as initial data. Verification of the model is done. The results obtained show relationships between the measured Doppler-polarimetric parameters and turbulence intensity.@en

New complexx adaptive algorithms of detection and measurement of turbulence intensity in weather formations are proposed. Algorithms are based on calculation of spectrum estimations by using the signals reflected from the adjacent range bins. Statistical hypothesis about the difference between the adjacent or next spectra are checked. The decision-making on distinction of spectra is done by the estimation of RMS velocities of Doppler spectra. Servicability and efficiency of new algorithms proves to be true by using statistical modeling as well as by processing real signals of weather radar.@en