Triple Estimation of Fractional Variable Order, Parameters, and State Variables Based on the Unscented Fractional Order Kalman Filter

In this paper, a method for states, parameters, and fractional order estimation is presented. The proposed method is an extension of the traditional dual estimation method and uses three blocks of filters with appropriate data interconnections. As the main part of the estimation algorithm, the Fractional Unscented Kalman Filter was used. The proposed Triple Estimation algorithm might be treated as a convenient tool for estimation and analysis of a wide range of dynamical systems with fractional constants or variable order nature, especially when knowledge about the identified system is very restricted and both order and system parameters are unknown. In order to show the performance of the proposed algorithm, sets of numerical results are presented.

A new bladed assembly simulator and an improved two-parameter plot method for blade tip-timing numerical simulations

The blade tip-timing measurement technique is presently the most promising technique for monitoring the blades of axial turbines and aircraft engines in operating conditions. Due to the high cost of experimental simulations of blade tip-timing–based condition monitoring methods, a numerical simulator for the vibrational behavior of bladed assemblies can be helpful for researchers interested in this field. So far, in most of the numerical simulators, the centrifugal effect of rotational speed on the natural frequencies is neglected. In this study, a new bladed assembly considering the centrifugal effect of the rotational speed for blade tip-timing numerical simulations is proposed. Moreover, an improvement in the engine order estimation algorithm in a two-parameter plot method is accomplished. In the assembly, blades are assumed to be cantilevered Euler–Bernoulli beams coupled together using linear springs. The finite element method is used to extract mass and stiffness matrices from differential equations of the system. By using the two-parameter plot method, the engine order of the excitation is detected. To examine the performance of the algorithm, Monte–Carlo simulation is implemented. The new simulator fulfills both cyclic symmetry and increase in the natural frequencies with increase in rotational speed. Engine order estimation with the new formulation in the two-parameter plot method is accurate. Hence, the new simulator and formulation for two-parameter plot method are reliable for numerical simulations.

Corner Reflector Network as a Geodetic Reference for Landslide Monitoring via InSAR Time Series: Case Study from Slovakia

<p>SAR interferometry (InSAR) is inherently a relative geodetic technique requiring one temporal and one spatial reference to obtain the datum-free estimates on millimetre-level displacements within the network of radar scatterers. To correct the systematic errors, such as the varying atmospheric delay, and solve the phase ambiguities, it relies on the first-order estimation network of coherent point scatterers (PS).</p><p>For vegetated and sparsely urbanized areas, commonly affected by landslides in Slovakia, it is often difficult to construct a reliable first-order estimation network, as they lack the PS. Purposedly deploying corner reflectors (CR) at such areas strengthens the estimation network and, if these CR are collocated with a Global Navigation Satellite Systems (GNSS), they provide an absolute geodetic reference to a well-defined terrestrial reference frame (TRF), as well as independent quality control.</p><p>For landslides, line-of-sight (LOS) InSAR displacements can be difficult to interpret. Using double CR, i.e. two reflectors for ascending/descending geometries within a single instrument, enables the assumption-less decomposition of the observed cross-track LOS displacements into the vertical and the horizontal displacement components.</p><p>In this study, we perform InSAR analysis on the one-year of Sentinel-1 time series of five areas in Slovakia, affected by landslides. 24 double back-flipped trihedral CR were carefully deployed at these sites to form a reference network, guaranteeing reliable displacement information over the critical landslide zones. To confirm the measurement quality, we show that the temporal average Signal-to-Clutter Ratio (SCR) of the CR is better than 20 dB. The observed CR motions in vertical and east-west directions vary from several millimetres up to 3 centimetres, with average standard deviation better than 0.5 mm.<br>Repeated GNSS measurements of the CR confirm the displacement observed by the InSAR, improve the positioning precision of the nearby PS, and attain the transformation into the national TRF.</p>

Identification of a HCHO signal in S5P/TROPOMI data over shipping lanes in the Indian Ocean

<p>Formaldehyde (HCHO) is an operational L2 product of the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor platform (S5P) (De Smedt et al., 2018).</p><p>International shipping is a significant source of pollutants including CO2, nitrogen oxides (NOx), sulfur oxides (SOx), volatile organic compounds, particulate matter, and black carbon. Shipping lanes are well known to be detected in NO<sub>2</sub> satellite observations (e.g., Beirle et al., 2004; Richter et al., 2004, 2011; Vinken et al 2014, Georgoulias et al., 2019). SO2 signal from ships has also been reported in OMI SO2 observations (Theys et al. 2014). However, so far only one study has reported the detection of an HCHO signal from ships using GOME-1 observations (Marbach et al. 2009). In a recent paper, it has been shown that the TROPOMI measurements allow for the detection of NO<sub>2</sub> pollution plumes from individual ships (Georgoulias et al., 2020).</p><p>In this work, we investigate the detection of a HCHO signal over shipping lanes in the Indian Ocean. When averaging several months of TROPOMI HCHO observations, at least two shipping lanes are clearly visible in the Indian Ocean. They are located over known shipping corridors from India and from Africa. We estimate the intensity of the HCHO columns along those tracks as a function of the season. We compare their location and relative intensity with TROPOMI NO2 observations. The possible impact of the a priori profiles is considered, as well as the impact of cloud filtering. Wind fields, which have been recently added in the HCHO L2 files, are used in order to study the intensity of the signal as a function of wind speeds. The HCHO background transported from continental sources is removed using a first-order estimation. The OMI QA4ECV HCHO and NO2 datasets between 2005 and 2020 are included in the analysis using 5 years averaged data, in order to study possible changes in the respective line intensities and locations. The detection of such a small signal is an illustration of the improved detection limit of HCHO columns with TROPOMI measurements.</p>