Microwave and Radar Week (MRW 2020): Selected Papers

The 9th Microwave and Radar Week (MRW 2020) was held in Warsaw the capital of Poland, on 5–7 October 2020 [...

Influence of Drift on Efficiency of Optimal Analog Adaptive Communication Systems with Feedback and Its Compensation

Results of analysis of drift influence on operation and efficiency of optimal analog adaptive communication systems with feedback and a new approach to drift compensation in these systems are presented in the paper. The proposed approach is based on application of the extended multidimensional adaptive algorithm that estimates simultaneously the value of a transmitted sample and the value of an unknown drift rate. The knowledge of the drift rate enables drift compensation and improves transmission efficiency of systems suffering problems related to drifts

Influence of Drift on Efficiency of Optimal Analog Adaptive Communication Systems with Feedback and Its Compensation

Results of analysis of drift influence on operation and efficiency of optimal analog adaptive communication systems with feedback and a new approach to drift compensation in these systems are presented in the paper. The proposed approach is based on application of the extended multidimensional adaptive algorithm that estimates simultaneously the value of a transmitted sample and the value of an unknown drift rate. The knowledge of the drift rate enables drift compensation and improves transmission efficiency of systems suffering problems related to drifts

A New Approach to Detecting Atrial Fibrillation Using Count Statistics of Relative Changes between Consecutive RR Intervals

Background: The ratio of the difference between neighboring RR intervals to the length of the preceding RR interval (x%) represents the relative change in the duration between two cardiac cycles. We investigated the diagnostic properties of the percentage of relative RR interval differences equal to or greater than x% (pRRx%) with x% in a range between 0.25% and 25% for the distinction of atrial fibrillation (AF) from sinus rhythm (SR). Methods: We used 1-min ECG segments with RR intervals with either AF (32,141 segments) or SR (32,769 segments) from the publicly available Physionet Long-Term Atrial Fibrillation Database (LTAFDB). The properties of pRRx% for different x% were analyzed using the statistical procedures and metrics commonly used to characterize diagnostic methods. Results: The distributions of pRRx% for AF and SR differ significantly over the whole studied range of x% from 0.25% to 25%, with particularly outstanding diagnostic properties for the x% range of 1.5% to 6%. However, pRR3.25% outperformed other pRRx%. Firstly, it had one of the highest and closest to perfect areas under the curve (0.971). For pRR3.25%, the optimal threshold for distinction AF from SR was set at 75.32%. Then, the accuracy was 95.44%, sensitivity was 97.16%, specificity was 93.76%, the positive predictive value was 93.85%, the negative predictive value was 97.11%, and the diagnostic odds ratio was 514. The excellent diagnostic properties of pRR3.25% were confirmed in the publicly available MIT–BIH Atrial Fibrillation Database. In a direct comparison, pRR3.25% outperformed the diagnostic properties of pRR31 (the percentage of successive RR intervals differing by at least 31 ms), i.e., so far, the best single parameter differentiating AF from SR. Conclusions: A family of pRRx% parameters has excellent diagnostic properties for AF detection in a range of x% between 1.5% and 6%. However, pRR3.25% outperforms other pRRx% parameters and pRR31 (until now, probably the most robust single heart rate variability parameter for AF diagnosis). The exquisite pRRx% diagnostic properties for AF and its simple computation make it well-suited for AF detection in modern ECG technologies (mobile/wearable devices, biopatches) in long-term monitoring. The diagnostic properties of pRRx% deserve further exploration in other databases with AF

Statistical and Diagnostic Properties of pRRx Parameters in Atrial Fibrillation Detection

Background: We studied the diagnostic properties of the percentage of successive RR intervals differing by at least x ms (pRRx) as functions of the threshold value x in a range of 7 to 195 ms for the differentiation of atrial fibrillation (AF) from sinus rhythm (SR). Methods: RR intervals were measured in 60-s electrocardiogram (ECG) segments with either AF (32,141 segments) or SR (32,769 segments) from the publicly available Physionet Long-Term Atrial Fibrillation Database (LTAFDB). For validation, we have used ECGs from the Massachusetts Institute of Technology–Beth Israel Hospital (MIT–BIH) Atrial Fibrillation Database. The pRRx distributions in AF and SR in relation to x were studied by histograms, along with the mutual association by the nonparametric Spearman correlations for all pairs of pRRx, and separately for AF or SR. The optimal cutoff values for all pRRx were determined using the receiver operator curve characteristic. A nonparametric bootstrap with 5000 samples was used to calculate a 95% confidence interval for several classification metrics. Results: The distributions of pRRx for x in the 7–195 ms range are significantly different in AF than in SR. The sensitivity, specificity, accuracy, and diagnostic odds ratios differ for pRRx, with the highest values for x = 31 ms (pRR31) rather than x = 50 (pRR50), which is most commonly applied in studies on heart rate variability. For the optimal cutoff of pRR31 (68.79%), the sensitivity is 90.42%, specificity 95.37%, and the diagnostic odds ratio is 194.11. Validation with the ECGs from the MIT–BIH Atrial Fibrillation Database confirmed our findings. Conclusions: We demonstrate that the diagnostic properties of pRRx depend on x, and pRR31 outperforms pRR50, at least for ECGs of 60-s duration

Beamforming of LOFAR Radio-Telescope for Passive Radiolocation Purposes

This paper presents the results of investigations on the beamforming of a low-frequency radio-telescope LOFAR which can be used as a receiver in passive coherent location (PCL) radars for aerial and space object detection and tracking. The use of a LOFAR radio-telescope for the passive tracking of space objects can be a highly cost-effective solution due to the fact that most of the necessary equipment needed for passive radiolocation already exists in the form of LOFAR stations. The capability of the radiolocation of planes by a single LOFAR station in Borowiec is considered to be ‘proof of concept’ for future research focused on the localization of space objects. Beam patterns of single sets of LOFAR antennas (known as tiles), as well as for the entire LOFAR station, are presented and thoroughly discussed in the paper. Issues related to grating lobes in LOFAR beam patterns are also highlighted. A beamforming algorithm used for passive radiolocation purposes, exploiting data collected by a LOFAR station, is also discussed. The results of preliminary experiments carried out with real signals collected by the LOFAR station in Borowiec, Poland confirm that the appropriate beamforming can significantly increase the radar’s detection range, as well as the detection’s certainty

Impact of EEG Frequency Bands and Data Separation on the Performance of Person Verification Employing Neural Networks

The paper is devoted to the study of EEG-based people verification. Analyzed solutions employed shallow artificial neural networks using spectral EEG features as input representation. We investigated the impact of the features derived from different frequency bands and their combination on verification results. Moreover, we studied the influence of a number of hidden neurons in a neural network. The datasets used in the analysis consisted of signals recorded during resting state from 29 healthy adult participants performed on different days, 20 EEG sessions for each of the participants. We presented two different scenarios of training and testing processes. In the first scenario, we used different parts of each recording session to create the training and testing datasets, and in the second one, training and testing datasets originated from different recording sessions. Among single frequency bands, the best outcomes were obtained for the beta frequency band (mean accuracy of 91 and 89% for the first and second scenarios, respectively). Adding the spectral features from more frequency bands to the beta band features improved results (95.7 and 93.1%). The findings showed that there is not enough evidence that the results are different between networks using different numbers of hidden neurons. Additionally, we included results for the attack of 23 external impostors whose recordings were not used earlier in training or testing the neural network in both scenarios. Another significant finding of our study shows worse sensitivity results in the second scenario. This outcome indicates that most of the studies presenting verification or identification results based on the first scenario (dominating in the current literature) are overestimated when it comes to practical applications

Experimental Verification of the Concept of Using LOFAR Radio-Telescopes as Receivers in Passive Radiolocation Systems

The paper presents a new idea of using a low-frequency radio-telescope belonging to the LOFAR network as a receiver in a passive radar system. The structure of a LOFAR radio-telescope station is described in the context of applying this radio-telescope for detection of aerial (airplanes) and space (satellite) targets. The theoretical considerations and description of the proposed signal processing schema for the passive radar based on a LOFAR radio-telescope are outlined in the paper. The results of initial experiments verifying the concept of a LOFAR station use as a receiver and a commercial digital radio broadcasting (DAB) transmitters as illuminators of opportunity for aerial object detection are presented