Design of a Novel Antenna Array Beamformer Using Neural Networks Trained by Modified Adaptive Dispersion Invasive Weed Optimization Based Data

A new antenna array beamformer based on neural networks (NNs) is presented. The NN training is performed by using optimized data sets extracted by a novel Invasive Weed Optimization (IWO) variant called Modified Adaptive Dispersion IWO (MADIWO). The trained NN is utilized as an adaptive beamformer that makes a uniform linear antenna array steer the main lobe towards a desired signal, place respective nulls towards several interference signals and suppress the side lobe level (SLL). Initially, the NN structure is selected by training several NNs of various structures using MADIWO based data and by making a comparison among the NNs in terms of training performance. The selected NN structure is then used to construct an adaptive beamformer, which is compared to MADIWO based and ADIWO based beamformers, regarding the SLL as well as the ability to properly steer the main lobe and the nulls. The comparison is made considering several sets of random cases with different numbers of interference signals and different power levels of additive zero-mean Gaussian noise. The comparative results exhibit the advantages of the proposed beamformer

Wavelet analysis applied on temporal data sets in order to reveal possible pre-seismic radio anomalies and comparison with the trend of the raw data

Since 2009, several radio receivers have been installed throughout Europe in order to realize the INFREP European radio network for studying the VLF (10-50 kHz) and LF (150-300 kHz) radio precursors of earthquakes. Precursors can be related to “anomalies” in the night-time behavior of VLF signals. A suitable method of analysis is the use of the Wavelet spectra. Using the “Morlet function”, the Wavelet transform of a time signal is a complex series that can be usefully represented by its square amplitude, i.e. considering the so-called Wavelet power spectrum. The power spectrum is a 2D diagram that, once properly normalized with respect to the power of the white noise, gives information on the strength and precise time of occurrence of the various Fourier components, which are present in the original time series. The main difference between the Wavelet power spectra and the Fourier power spectra for the time series is that the former identifies the frequency content along the operational time, which cannot be done with the latter. Anomalies are identified as regions of the Wavelet spectrogram characterized by a sudden increase in the power strength. On January 30, 2020 an earthquake with Mw= 6.0 occurred in Dodecanese Islands. The results of the Wavelet analysis carried out on data collected some INFREP receivers is compared with the trends of the raw data. The time series from January 24, 2020 till January 31, 2000 was analyzed. The Wavelet spectrogram shows a peak corresponding to a period of 1 day on the days before January 30. This anomaly was found for signals transmitted at the frequencies 19,58 kHz, 20, 27 kHz, 23,40 kHz with an energy in the peak increasing from 19,58 kHz to 23,40 kHz. In particular, the Powered by TCPDF (www.tcpdf.org) signal at the frequency 19,58 kHz, shows a peak on January 29, while the frequencies 20,27 kHz and 23,40 kHz are characterized by a peak starting on January 28 and continuing to January 29. The results presented in this work shows the perspective use of the Wavelet spectrum analysis as an operational tool for the detection of anomalies in VLF and LF signal potentially related to EQ precursors

Synthesis of a near-optimal high-gain antenna array with main lobe tilting and null filling using Taguchi initialized invasive weed optimization

A near-optimal base-station antenna array synthesis suitable for broadcasting applications is presented. The array is required to provide a high-gain radiation pattern with a main lobe slightly tilted from the horizontal plane and null filling inside an angular sector under the main lobe. To satisfy the above requirements, a novel invasive weed optimization (IWO) variant called Taguchi initialized IWO (TI-IWO) is proposed in this paper. In TI-IWO, the Taguchi’s optimization method is employed to initialize effectively the positions of the weeds used by the IWO method. In this way, the fitness function starts from lower values and, thus, the TI-IWO method finds better near-optimal solutions than the conventional IWO method. The proposed method has been applied to linear arrays. Due to its easy implementation in practice, a uniform-amplitude excitation distribution is considered to be applied on the array elements. Two cases of isotropic source arrays are studied under specific requirements for maximum possible gain, main lobe tilting, and null filling. Also, the TI-IWO method is applied to optimize realistic cases of collinear wire dipole arrays in front of a mast under the same requirements and an additional one concerning the impedance matching of all the dipoles

The INFREP Network: Present Situation and Recent Results

VLF/LF (20 - 300 kHz) radio waves propagation is affected by different factors such as meteorological conditions, solar bursts and geomagnetic activity. At the same time, variations of some parameters in the ground, in the atmosphere and in the ionosphere occurring during the preparatory phase of earthquakes can produce disturbances in the propagation of the previous signals along their radio paths: these disturbances are the radio precursors. Since 2009, several VLF/LF radio receivers have been installed throughout Europe in order to realize a European (VLF/LF) radio network for studying the VLF/LF radio precursors of earthquakes, called the INFREP network. In this paper, at first the description of the present situation of the INFREP network is presented, that is: the location of the receivers, the location of the VLF/LF transmitters whose signal is sampled, the daily download of the data collected by the receivers on the INFREP server and the method of data analysis used in order to individuate possible radio precursors. Then the results obtained on the occasion of recent (2016-2017) seismic activities which occurred in the “sensitive” zone of the INFREP network are presented. The first case examined is the October 30, 2016 earthquake with Mw = 6.5, which occurred in Central Italy, near Norcia small town; this earthquake was preceded by a strong shock (Mw = 5.9) which occurred 4 days before. The second case presented is the strong (Mw = 6.7) offshore earthquake which occurred on July 20, 2017, near the coast of Turkey and Kos island (Greece) and the third case is the August 8, 2017 earthquake with Mw = 5.0, which also occurred near the coast of Turkey and Kos island (Greece). In all the previous cases radio anomalies were revealed in some radio signals collected by the receiver located in Cyprus. The influence of causes different from seismicity as geomagnetic activity and solar burst, meteorological conditions, malfunction of the receiver and/or the transmitters has been examined and none convincing connections appeared. So, the possibility that the previous anomalies are radio precursors of the earthquakes seems realistic. Finally, some discrepancy of some of these anomalies with respect to the general peculiarities of the radio precursors is presented and discussed

Pre-seismic radio anomalies observed on the occasion of the Mw= 6.7 and Mw = 5.0 earthquakes occurred offshore near the southwest coast of Turkey on July-August, 2017

The INFREP radio network has been operational in Europe since 2009, in order to reveal possible radio precursors of earthquakes. Currently the network is consisted of ten receivers. There are two receivers located in Italy, two in Romania and two in Greece whereas Austria, Portugal, Cyprus and Georgia have one each. The receivers, realized by an Italian factory, can measure the intensity of 10 radio signals in the VLF (10-50 kHz) and LF (150-300 kHz) bands. On July 20, 2017 a strong (Mw=6.7) earthquake occurred offshore, near the coast of Turkey and Kos island (Greece); on August 8 an earthquake with Mw=5.0 occurred practically in the same zone. The focal depth was 10 km for both the events. The epicentres are inside the “sensitive” area of the INFREP network. On both the occasions, evident pre-seismic disturbances were pointed out in the DHO (23.4 kHz) signal collected by the Cyprus receiver. On November 7, an earthquake with Mw =5.1 occurred offshore at about 120 km from the previous ones, on south-east direction. Also in this case an anomaly was observed on the quoted signal. The focal depth of the earthquake was 70 km, large enough to produce detectable anomalies; in addition a more evident anomaly appeared on the DHO radio signal collected by the Crete receiver, the sensitive Fresnel zone of which is out the epicentre area of the earthquake. These circumstances suggest a possible cause of the anomalies different from the seismicity and indeed a disturbed meteorological situation pointed out. All the anomalies we present, were revealed by the on-line warning system based on the Wavelet analysis, planned and realized in the frame of the INFREP cooperation