Auto-Tracking Wireless Power Transfer System With Focused-Beam Phased Array

This article used image recognition and beam forming technology to build a phased array with target tracking and transmitting the microwaves with a focused beam. The coordinate position of the target is obtained from the image recognition module and converted into phase information for the phased array. This system was constructed by a 1 × 4 5.764-GHz phased array with four 4-bit phase shifters. The phase shifters created a focused beam, which requires not only the target’s direction angle but also the transmission distance. The target position as well as direction and distance information were gathered using image recognition. The tracking beam method was evaluated by simulation and actual measurement. The results showed that the focused beam can always be formed in real time to track the target. The transfer efficiency of the focused beam was improved higher than that of uniform phase beam within a distance of 50 cm. The automatic tracking power transmission system has a response time of about 100 ms

Experimental path loss models for UWB multistatic radar systems

The use of Ultra-Wideband (UWB) radio technology in a multistatic radar system has recently gained interest to implement Wireless Sensor Networks (WSN) capable of detecting and tracking targets in indoor environments. Due to the increasing attention towards multistatic UWB systems, it is important to perform the radio channel characterization. In this thesis we focus on the characterization of the path loss exponent (α). To perform the present work, the followed methodology was to collect experimental data from the UWB devices using a suitable target, this information was processed with a clutter removal algorithm using the Empty Room (ER) approach, then the contribution of the target was isolated to produce a graph of energy as a function of the product between the target-to-transmitter and the target-to-receiver distances in a bistatic configuration. Finally, using this plot it was properly obtained the value of the path loss exponent. As as additional experimental result, the main statistical parameters associated to the residual clutter were calculated, which are expected to allow having a better understanding and characterization of the radar system performance in the experimental environments

Multiple Sensor Linear Multi-Target Integrated Probabilistic Data Association for Ultra-Wide Band Radar

Ultra-Wide Band (UWB) radar has a number of advantages of resolving multipath, exceptional spatial resolution, and ranging performance. However, several difficulties are confronted for multiple target tracking using UWB radars such as clutter signals which contaminate target signals, and unidentified number and behavior of the targets. Hence, this paper presents to develop a multiple moving target tracking algorithm, consisting of preprocessing and multiple target tracking steps. In the preprocessing step, static clutter reduction and constant false alarm rate (CFAR) detection extract the target candidate range measurements from each UWB radar. Then, two multiple target tracking (MTT) steps are developed: range- based MTT and position-based MTT. The range-based MTT is mainly based on existing linear multi-target integrated probabilistic data association (LM-IPDA) from each UWB radar measurement. Then the outputs of each LM-IPDA are gathered in the positioning center to estimate the position of multiple targets. On the other hands, the position-based MTT is based on multiple sensor LM-IPDA (msLM-IPDA) as an accurate target tracking method for various uncertainties by improving the probabilistic model of LM-IPDA. The tracking performance of two MTT methods is investigated with both numerical simulation and experiments

one6G white paper, 6G technology overview:Second Edition, November 2022

6G is supposed to address the demands for consumption of mobile networking services in 2030 and beyond. These are characterized by a variety of diverse, often conflicting requirements, from technical ones such as extremely high data rates, unprecedented scale of communicating devices, high coverage, low communicating latency, flexibility of extension, etc., to non-technical ones such as enabling sustainable growth of the society as a whole, e.g., through energy efficiency of deployed networks. On the one hand, 6G is expected to fulfil all these individual requirements, extending thus the limits set by the previous generations of mobile networks (e.g., ten times lower latencies, or hundred times higher data rates than in 5G). On the other hand, 6G should also enable use cases characterized by combinations of these requirements never seen before, e.g., both extremely high data rates and extremely low communication latency). In this white paper, we give an overview of the key enabling technologies that constitute the pillars for the evolution towards 6G. They include: terahertz frequencies (Section 1), 6G radio access (Section 2), next generation MIMO (Section 3), integrated sensing and communication (Section 4), distributed and federated artificial intelligence (Section 5), intelligent user plane (Section 6) and flexible programmable infrastructures (Section 7). For each enabling technology, we first give the background on how and why the technology is relevant to 6G, backed up by a number of relevant use cases. After that, we describe the technology in detail, outline the key problems and difficulties, and give a comprehensive overview of the state of the art in that technology. 6G is, however, not limited to these seven technologies. They merely present our current understanding of the technological environment in which 6G is being born. Future versions of this white paper may include other relevant technologies too, as well as discuss how these technologies can be glued together in a coherent system

Sensor Radar for Object Tracking

Precise localization and tracking of moving objects is of great interest for a variety of emerging applications including the Internet-of-Things (IoT). The localization and tracking tasks are challenging in harsh wireless environments, such as indoor ones, especially when objects are not equipped with dedicated tags (noncollaborative). The problem of detecting, localizing, and tracking noncollaborative objects within a limited area has often been undertaken by exploiting a network of radio sensors, scanning the zone of interest through wideband radio signals to create a radio image of the objects. This paper presents a sensor network for radio imaging (sensor radar) along with all of the signal processing steps necessary to achieve highaccuracy objects tracking in harsh propagation environments. The described sensor radar is based on the impulse radio (IR) ultrawideband (UWB) technology, entailing the transmission of very short duration pulses. Experimental results with actual UWB signals in indoor environments confirm the sensor radar's potential in IoT applications