In order to identify the modal parameters of civil structures it is vital to distinguish the defective data from that of appropriate and accurate data. The defects in data may be due to various reasons like defects in the data collection, malfunctioning of sensors, etc. For this purpose Exploratory Data Analysis (EDA) was engaged toenvisage the distribution of sensor’s data and to detect the malfunctioning with in the sensors. Then outlier analysis was performed to remove those data points which may disrupt the accurate data analysis. Then Data Driven Stochastic Sub-space Identification (DATA-SSI) was engaged to perform the modal parameter identification. In the end to validate the accuracy of the proposed method stabilization diagrams were plotted. Sutong Bridge, one of the largest span cable stayed bridge was used as a case study and the suggested technique was employed. The results obtained after employing the above mentioned techniques are very valuable, accurate and effective.

The paper presents the results of investigating the effect of increase of observation correlations on detectability and identifiability of a single gross error, the outlier test sensitivity and also the response-based measures of internal reliability of networks. To reduce in a research a practically incomputable number of possible test options when considering all the non-diagonal elements of the correlation matrix as variables, its simplest representation was used being a matrix with all non-diagonal elements of equal values, termed uniform correlation. By raising the common correlation value incrementally, a sequence of matrix configurations could be obtained corresponding to the increasing level of observation correlations. For each of the measures characterizing the above mentioned features of network reliability the effect is presented in a diagram form as a function of the increasing level of observation correlations. The influence of observation correlations on sensitivity of the w -test for correlated observations (Förstner 1983,Teunissen 2006) is investigated in comparison with the original Baarda’s w -test designated for uncorrelated observations, to determine the character of expected sensitivity degradation of the latter when used for correlated observations. The correlation effects obtained for different reliability measures exhibit mutual consistency in a satisfactory extent. As a by-product of the analyses, a simple formula valid for any arbitrary correlation matrix is proposed for transforming the Baarda’s w -test statistics into the w -test statistics for correlated observations.

The paper presents a general concept of geodetic observations adjustment based on application of the Edgeworth' series and the principle of an alternative choice. The Edgeworth' series approximates the empirical distribution of measurement errors and gives an opportunity to modify the empirical characteristics of errors distribution. The method of estimation used is based on the principle of the alternative choice. Its natural robustness for outliers was the basis for newly created method called PAC-E. The paper presents the algorithm and some numerical tests that were carried out to compare the results of the proposed method with the results of the classical LS adjustment. Special attention was paid on the effect of non-zero excess and robustness of the proposed method.

The aim of this paper is to compare the efficiency of various outlier correction methods for ECG signal processing in biometric applications. The main idea is to correct anomalies in various segments of ECG waveform rather than skipping a corrupted ECG heartbeat in order to achieve better statistics. Experiments were performed using a self-collected Lviv Biometric Dataset. This database contains over 1400 records for 95 unique persons. The baseline identification accuracy without any correction is around 86%. After applying the outlier correction the results were improved up to 98% for autoencoder based algorithms and up to 97.1% for sliding Euclidean window. Adding outlier correction stage in the biometric identification process results in increased processing time (up to 20%), however, it is not critical in the most use-cases.

Day-boundary discontinuity (DBD) is an effect present in precise GNSS satellite orbit and clock products originating from the method used for orbit and clock determination. The non-Gaussian measurement noise and data processing in 24 h batches are responsible for DBDs. In the case of the clock product, DBD is a time jump in the boundary epochs of two adjacent batches of processed data and its magnitude might reach a couple of ns. This article presents the four GNSS (Global Navigation Satellite System) systems DBD analysis in terms of change over an 8 year period. For each of 118 satellites available in this period, the yearly value of DBD was subject to analysis including standard deviation and frequency of outliers. Results show that the smallest DBDs appear in the GPS system, the biggest – for the BeiDou space segment. Moreover, the phenomenon of changes in DBDs over time is clearly seen at the beginning of the analysed period when the magnitude and number of the DBDs were larger than for current, newest clock products