This paper proposes a study of underwater noise in Siutghiol lake from Constanta. This study is useful for the signal to noise ratio maximization for better underwater targets detection. Studying the properties of the underwater noise we want to conclude about noise stationery, in large or even in the restraint sense. It is very useful to study the aspect of the stochastic parameters – mean value, standard deviation and correlation coefficients. The relative invariance of those parameters denotes a kind of noise stationary in wide sense. If the density probability function of the underwater noise is time invariant this one can be considered a restraint (strict) sense stationary one. The noise characterization is useful to optimize the underwater targets detection by SONAR systems, using classic matched filters or time-frequency matched filters.
Underwater digital communication and sonars rely on basic signal detection. The problem with underwater signal detection is that of the extremely expensive equipments. In this paper we propose both a low cost solution for signal detection, which practically consists in integrating and adapting the already existing equipments and methods for underwater noise analysis.
This work provides an experimental implementation of the cognitive software-defined Doppler radar based on the low cost USRP platform developed by Ettus Research. The proposed solution employs spectrum sensing in order to take advantage of the white spaces of the radio spectrum. The system continuously adapts its operating frequency according to environment changes, reducing the risk of interfering with other radio systems and acquiring a higher degree of immunity against jamming. The novelty of the proposed algorithm used for dynamically allocating the system’s operating frequency lies in its ability of covering a wide frequency bandwidth despite of the reduced instantaneous bandwidth of the low cost USRP platform employed in the experimental setup. Another related advantage of the proposed algorithm is the reduced computational power required for the real-time operation of the system. All of the above mentioned assertions have been validated experimentally.
Due to the technology development, navigation systems are widely used in ground vehicle applications such as position prediction, safety of life, etc. It is known that a hybrid navigation system consisting of a GPS and inertial navigation system (INS) can provide a more accurate position prediction.
By applying a Method of Moments (MoM) approach on the acquired data with INS/GPS we can extract both the coordinate and important information concerning safety of life. This kind of system will be cost effective and can also be used as a black box on boats, cars, submersible ships and even on small aircrafts.
This paper proposes an analysis, especially in time domain, of the electrical noise existent on the power distribution lines. This study is important for the use of powerlines as a channel of information transmissions. This information may refer to analog signals and as well to digital signals. The main problem addressed in this paper consists in the characterization of the background noise and to establish his statistical proprieties. It is very important to know if the noise induced in the transmission channel is a stationary one, or even an ergodic one. The main parameters like the mean value, the mean square value were determined in this paper. The approximation of the probability density function of each statistical parameter was studied. The pulses induced in the transmission channel by the transient phenomena of the power electrical systems were considered deterministic signals and their contributions were not included in this study.
KEYWORDS: Robotics, Radio propagation, Buildings, Data modeling, Robotics, Data acquisition, Receivers, Non-line-of-sight propagation, Environmental sensing, Global Positioning System, Mobile devices
This paper deals with the use of autonomous robotic platforms able to locate radio signal sources such as mobile phones, buried under collapsed buildings as a result of earthquakes, natural disasters, terrorism, war, etc. This technique relies on averaging position data resulting from a propagation model implemented on the platform and the data acquired by robotic platforms at the disaster site. That allows us to calculate the approximate position of radio sources buried under the rubble. Based on measurements, a radio map of the disaster site is made, very useful for locating victims and for guiding specific rubble lifting machinery, by assuming that there is a victim next to a mobile device detected by the robotic platform; by knowing the approximate position, the lifting machinery does not risk to further hurt the victims. Moreover, by knowing the positions of the victims, the reaction time is decreased, and the chances of survival for the victims buried under the rubble, are obviously increased.
Antenna gain is usually evaluated under far-field conditions. Furthermore, Friis transmission formula can solely be applied when antenna size can be neglected with respect to the distance between the measuring antenna and the antenna under test. In this paper, we show that by applying the distance averaging technique the far-field and antenna size constraints can be overcome. Our method was validated by measuring a monopole antenna and a Vivaldi antenna in an open area test site (OATS).
KEYWORDS: Signal detection, Time-frequency analysis, Sensors, Interference (communication), Signal analyzers, Signal to noise ratio, Electronic filtering, Fourier transforms, Linear filtering, Antennas
In this paper we propose an analysis of the possibilities of spikes detection which appears on the power lines of electrical distribution. The importance of this problem consists in the possibility of surveillance at distance the regimes of power electrical motors. This regime was studied in an industrial network which supplies the power pumps necessary to assures a city water consumption. We consider the industrial electrical networks as a linear, time invariant and causal system which has a certain response to the electrical spikes, assimilates with Dirac impulses. For that reason the output signal represents the impulse response of the system. The main problem is to detect this signal and to establish the moments of its presence. To detect and extract the useful signal linear methods like fourier transform or Short Time Fourier Analysis are not very relevant. A more efficient method to detect the spikes presence consists in using quadratic detectors in timefrequency domain, like detectors based on Wigner-Ville transform or detectors based on Ambiguity Function. In this paper we tried to present the advantages of these last detectors.
KEYWORDS: Data processing, Data acquisition, Computer simulations, Analytical research, General applications engineering, Instrument modeling, Data modeling, Calculus, Data storage, Mathematical modeling
Experimental data processing is an issue that must be solved in almost all the domains of science. In engineering we usually have a large amount of data and we try to extract the useful signal which is relevant for the phenomenon under investigation. The criteria used to consider some points more relevant then some others may take into consideration various conditions which may be either phenomenon dependent, or general. The paper presents some of the ideas and tests regarding the identification of the best set of criteria used to filter the initial set of points in order to extract a subset which best fits the approximated function. If the function has regions where it is either constant, or it has a slow variation, fewer discretization points may be used. This means to create a simpler solution to process the experimental data, keeping the accuracy in some fair good limits.
Direction finding and attitude determination is of utmost importance for marine, aerial, spatial and land-based navigation [1], as well as control of vehicles, in surveying and in target acquisition of tracking radars. These problems can be solved using dedicated sensors commonly named as compasses and rate gyros. Unfortunately, the classical means of attitude determination both by magnetic and gyrocompasses become unusable at extreme latitudes. Furthermore, gyrocompasses inherently yield erroneous results on high speed craft. Three-axis attitude of a vehicle can be determined using a GPS receiver with multiple antennas, by measuring carrier phases [2], signal strength [3], or integrated INS/GPS systems [4]. This paper proposes a new method of attitude determination using two low-cost GPS receivers.
In this paper we propose the use of frequency selective surfaces based on meander line radiators, as targets for monitoring slow displacements with synthetic aperture radars. The optimization of the radiators is performed by using genetic algorithms on only two parameters i.e., gain and size. As an example, we have optimized a single meander antenna, resonating in the X-band, at 9.65 GHz.
In this paper we present a type of antipodal Vivaldi antenna design, which can be used for pulse radiation in UWB communication. The Vivaldi antenna is a special tapered slot antenna with planar structure which is easily to be integrated with transmitting elements and receiving elements to form a compact structure. When the permittivity is very large, the wavelength of slot mode is so short that the electromagnetic fields concentrate in the slot to form an effective and balanced transmission line. Due to its simple structure and small size the Vivaldi antennas are one of the most popular designs used in UWB applications. However, for a two-antenna radar system, there is a high mutual coupling between two such antennas due to open configuration. In this paper, we propose a new method for reducing this effect. The method was validated by simulating a system of two Vivaldi antennas in front of a standard target.
In this paper, we propose an approach of optimization of meander line antennas by using genetic algorithm. Such antennas are used in RFID applications. As opposed to other approaches for meander antennas, we propose the use of only two optimization objectives, i.e. gain and size. As an example, we have optimized a single meander dipole antenna, resonating at 869 MHz.
This paper proposes a novel UWB antenna system for spark detection and localization by using the amplitude comparison direction finding (DF) method. The proposed design consists of two identical axially crossed "padlock” shaped UWB antennas, with unbalanced feeding. Simulation results show that such radiating systems can be used for assessing the direction of arrival for short pulses.
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