Ultra Wide Band localization and tracking hybrid technique using VRTs

This research presents hybrid radar tracking technique consisting of Time Of Arrival (TOA) and Received Signal Strength (RSS) techniques. This hybrid design increases efficiency, accuracy and sensitivity of radar system. The radar used in this research is multistatic radar with one transmitter and three receivers. One common drawback in RSS and TOA techniques is high level synchronization in transmitter and receivers. The hybrid design also suffers from transmitter-receiver synchronization. To overcome TX-RX synchronization problem Virtual Reference Tags (VRTs) are used. These tags are virtually mapped over the surveillance area giving radar design different reference points from which it can accurately locate intruder and monitor its movements. Also four cases of differen

Ultra Wide-Band Localization and SLAM: A Comparative Study for Mobile Robot Navigation

In this work, a comparative study between an Ultra Wide-Band (UWB) localization system and a Simultaneous Localization and Mapping (SLAM) algorithm is presented. Due to its high bandwidth and short pulses length, UWB potentially allows great accuracy in range measurements based on Time of Arrival (TOA) estimation. SLAM algorithms recursively estimates the map of an environment and the pose (position and orientation) of a mobile robot within that environment. The comparative study presented here involves the performance analysis of implementing in parallel an UWB localization based system and a SLAM algorithm on a mobile robot navigating within an environment. Real time results as well as error analysis are also shown in this work

Hybrid Data Fusion Techniques for Localization in UWB Networks

International audienceIn this paper, we exploit the concept of data fusion in UWB (Ultra Wide Band) localization systems by using different location-dependent observables. We combine ToA (Time of Arrival) and RSS (Received Signal Strength) in order to get accurate positioning algorithms.We assume that RSS observables are usually available and we study the effect of adding ToA observables on the positioning accuracy. The proposed architecture of Hybrid Data Fusion (HDF) is based on two stages: Ranging using RSS and ToA; and Estimation of position by the fusion of estimated ranges. In the first stage, we propose a new estimator of ranges from RSS observables assuming a path loss model. In the second stage, a new ML estimator is developed to merge different ranges with different variances. In order to evaluate these algorithms, simulations are carried out in a generic indoor environment and Cramer Rao Lower Bounds (CRLB) are investigated. Those algorithms show enhanced positioning results at reasonable noise levels

An efficient iris image thresholding based on binarization threshold in black hole search method

In iris recognition system, the segmentation stage is one of the most important stages where the iris is located and then further segmented into outer and lower boundary of iris region. Several algorithms have been proposed in order to segment the outer and lower boundary of the iris region. The aim of this research is to identify the suitable threshold value in order to locate the outer and lower boundaries using Black Hole Search Method. We chose these methods because of the ineffient features of the other methods in image indetification and verifications. The experiment was conducted using three data set; UBIRIS, CASIA and MMU because of their superiority over others. Given that different iris databases have different file formats and quality, the images used for this work are jpeg and bmp. Based on the experimentation, most suitable threshold values for identification of iris aboundaries for different iris databases have been identified. It is therefore compared with the other methods used by other researchers and found out that the values of 0.3, 0.4 and 0.1 for database UBIRIS, CASIA and MMU respectively are more accurate and comprehensive. The study concludes that threshold values vary depending on the database

Properties of leaky waves supported by grounded dielectric super-layers and implications on the design of reflector feeds

The design strategy that uses dielectric super-layers with neighboring wave-guides closed in matched loads constitutes a worst case scenario as far as the performance enhancement is concerned and finds applicability in radiometric imaging arrays. On the other side the design strategy that uses dielectric super-layers with neighboring wave-guides closed in properly tuned reactive loads can be seen as best case scenario representative of a multi beam system for a telecommunication satellite with independent channels

Design of a Low Loss Metallo-Dielectric EBG Waveguide at Submillimeter Wavelengths

In this letter we show the viability of using concentric cylindrically-periodic (CP) dielectrics to realize low-loss propagation at submillimeter wavelengths. Most of the power in the CP Waveguide (WG) is confined to an air core propagating a TE_(01) mode. The TM_(11) mode degeneracy is removed over a very wide bandwidth by a series of periodically spaced dielectric rings that are optimized in thickness and spacing. The new waveguide differs from classical Bragg fibers in that we use only a small number of dielectric layers (2-4), and terminate the outer layer with an external metal coating. We include several designs and describe the optimization procedure that was used to realize structures with low propagation and bend loss

Spectral Evidence of Ice on Aircrafts – The SEI Project

The general objective of the SEI project (reference call: MANUNET III 2018) is to experiment spectral sensor fusion techniques of data acquired by UAVs (Unmanned Aerial Vehicles) during aircraft preflight inspection. In General Aviation, an important safety issue regards the presence of ice on the aircraft's fuselage and wings. Ice on the wings can cause loss of lift and stalling, which in most cases would result, during take-off phase, in airplane’s fatal crash. Another important aspect to consider is the high amount of de-icing liquid usually involved in the process incurring in high costs and considerable damage to the environment. This is not a typical industrial scenario, but the project addresses important aspects related to the manufacturing sector: it has to accomplish specific tasks following a design process; it involves human operators (labour) collaborating with machines and tools; it includes the usage of semi-raw materials (glycol fluids) to accomplish a service; it sees serialization of the process that could be invoked at any needed time. Moreover, it targets safety issues both for operators and machines regarding reliability of results at the end of the process, it is order-based and comparable to a discrete manufacturing process

Impact of on-body channel models on positioning success rate with UWB Wireless Body Area Networks

International audienceIn this paper, we aim to evaluate the positioning success rate of nodes placed on the body using different scheduling strategies at the Media Access Control (MAC) layer with Ultra Wide Band (UWB) Wireless Body Area Networks (WBAN) and under three different channel models. For this purpose, each node calculates its relative position with the estimation of its distances with the on-body anchors. Accordingly, the distance between two nodes can be estimated with the transmission of three packets, as defined by the '3-Way ranging' protocol (3-WR). However, these transactions can be affected by the WBAN channel leading into a packet loss and therefore positioning errors. In this work, we consider a PHY layer based on Impulse-Radio UWB (IR-UWB) with three different channels: (a) a theoretical path loss channel model based on the on-body CM3 channel (Anechoic chamber), (b) a simulated channel calculated with the PyLayers ray-tracing simulator and (c) experimental traces obtained by measurement. Moreover, we analyze the positioning success rate using three scheduling strategies (Single node localization (P2P), Broadcast Single node localiza-tion (P2P-B) and Aggregated & Broadcast (A&B)) with a MAC layer based on time division multiple access (TDMA) and under a realistic pedestrian walking scenario. Our results show that the scheduling strategy with A&B let the nodes to estimate more positions even through channels with slow and fast fading

RL-DWA Omnidirectional Motion Planning for Person Following in Domestic Assistance and Monitoring

Robot assistants are emerging as high-tech solutions to support people in everyday life. Following and assisting the user in the domestic environment requires flexible mobility to safely move in cluttered spaces. We introduce a new approach to person following for assistance and monitoring. Our methodology exploits an omnidirectional robotic platform to detach the computation of linear and angular velocities and navigate within the domestic environment without losing track of the assisted person. While linear velocities are managed by a conventional Dynamic Window Approach (DWA) local planner, we trained a Deep Reinforcement Learning (DRL) agent to predict optimized angular velocities commands and maintain the orientation of the robot towards the user. We evaluate our navigation system on a real omnidirectional platform in various indoor scenarios, demonstrating the competitive advantage of our solution compared to a standard differential steering following