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.
As shown in another paper , we have imagined and built radio modules for path loss models calibration, to be integrated on autonomous robotic platforms or drones . Path loss models are very useful in disaster situations, helping to locate radio signal sources such as mobile phones, buried under collapsed buildings as a result of earthquakes, natural disasters, terrorism, war, etc.
For search and rescue scenarios [1,2], radio devices with precision comparable to laboratory instruments are needed. More than that, the modules have to be small enough to be integrated on autonomous robotic platforms  or drones, for search and rescue activities. Power consumption have to be small enough to sustain a reasonable time of autonomy. For this purpose, we have imagined two modules, a fixed frequency receiver and a wideband transceiver.
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.
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).
In this paper, we propose to extend the frequency-domain synthesis approach based on a variable slope profile for antennas with a linear variation over a fractional bandwidth in the order of 100%. In that case the inflection point on the resulting profile is no longer located at its half. Thus, the profile shape will no longer be folded at the half, but at a coordinate closer to the end, the resulting shape approaching to a bow-tie antenna than to a circular dipole antenna.
The log-normal propagation model is usually applied for scenarios including a line-of-sight path. However, there are many
cases that do not include such a propagation path, e.g. indoor transmission and disaster situations, when radio waves have
to penetrate trough ruins. In this paper, we show that the log-normal model can also be applied for non line-of-sight
transmission. Both indoor scenario and trough-ruins scenario, are investigated.
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.