This paper presents a tag identification system based on the detection of high-frequency acoustic signals by means of a portable device. A binary frequency shift keying-modulated code is used to tag the different locations. This code is preceded by a synchronizing chirp waveform that allows noncoherent detection even under strong Doppler frequency shifts. The proposed system is first characterized in terms of robustness against noise, coverage, Doppler tolerance, and intertag interference, making use of a modular simulator. This simulator is based on three basic stages that account for the frequency response of the emitter-receiver pair, the attenuation of acoustic signals in air, and the noncoherent demodulation. This system is then implemented in an Android-based platform and tested in a real scenario. The results of this experimental analysis show good agreement with the previous characterization, and they also confirm the feasibility of the proposed system to develop location-aware applications.

Proximity-Based Indoor Positioning Systems (PIPSs) are a simple to install alternative in large facilities. Besides, these systems have a reduced computational cost on the mobile device of those users who do not continuously demand a high location accuracy. This work presents the design of an Acoustic Low Energy (ALE) beacon based on the emission of inaudible Linear Frequency Modulated (LFM) signals. This coding scheme provides high robustness to in-band noise, thus ensuring a reliable detection of the beacon at a practical range, after pulse compression. A series of experimental tests have been carried out with nine different Android devices to study the system performance. These tests have shown that the ALE beacon can be detected at one meter distance with signal-to-noise ratios as low as −12 dB. The tests have also demonstrated a detection rate above 80% for reception angles up to 50° with respect to the beacon’s acoustic axis at the same distance. Finally, a study of the ALE beacon energy consumption has been conducted demonstrating comparable power consumption to commercial Bluetooth Low Energy (BLE) beacons. Besides, the ALE beacon search can save up to 9% more battery of the Android devices than the BLE beacon scanning.

Time-of-Flight cameras deals with distance measurements in a matrix, pixel by pixel. Every pixel, called smart pixel, makes use of analog technology to calculate correlations, and in such a way, it computes the phase difference between the emitted signal and the received one, both modulated in RF-range. The main drawback of these systems is their short working range, that depends on the wavelength of the modulating signal. This problem can be overcome by using a multi-camera system with different modulating frequencies, but then, the performance is adversely affected because of interference phenomena. One approach to deal with this situation consist of encoding the emissions with spreading sequences that exhibit good cross-correlations properties among them. The number of possible cameras depends on the correlations properties of the sequences. In this work, the performance of spreading sequences in terms of bandwidth and signal-to-noise ratio used in time-of-flight systems is presented. Kasami sequences are considered to be a good choice for multi-camera environment.

Self-calibrated Acoustic Local Positioning Systems (ALPS) generally require a high consumption of hardware and software resources to obtain the user’s position at an acceptable update rate. To address this limitation, this work proposes a self-calibrated ALPS based on a software/hardware co-design approach. This working architecture allows for efficient communications, signal processing tasks, and the running of the positioning algorithm on low-cost devices. This fact also enables the real-time system operation. The proposed system is composed of a minimum of four RF-synchronized active acoustic beacons, which emit spread-spectrum modulated signals to position an unlimited number of receiver nodes. Each receiver node estimates the beacons’ position by means of an auto-calibration process and then computes its own position by means of a 3D multilateration algorithm. A set of experimental tests has been carried out where the feasibility of the proposed system is demonstrated. In these experiments, accuracies below 0.1 m are obtained in the determination of the receptor node position with respect to the set of previously-calibrated beacons.

A system for making remote two- and three-dimensional reconstructions from computerized tomography images has been developed in order to improve medical teleteaching. It allows the automatic two- and three-dimensional remote visualization of the anatomical structure of interest. As a part of this system, software has been developed which allows many visual operations or transformations on a remote three-dimensional model. It permits the remote workstation and the local workstation to visualize every transformation simultaneously. It allows a doctor to interact virtually and remotely with the anatomical structure. The software enables examination of the anatomical model from all angles, even from inside (including planar and three-dimensional presentations).