Empirical Based Ranging Error Mitigation in IR-UWB: A Fuzzy Approach

Power efficient ultra-wideband based wireless communication for wireless body area network applications

In recent times, impulse-radio ultra-wideband (IR-UWB) systems have gained significant attention for indoor positioning and short-range radar applications due to many of their inherent properties like ultra-fine temporal resolution, non-line-of-sight detection, multipath immunity, low power consumption, low-cost, etc. The critical challenge for the IR-UWB based systems is to generate an IR-UWB pulse, which is shorter in time and higher in amplitude. In particular, for the indoor-ranging and radar applications, the limited peak power of an IR-UWB pulse restricts the line-of-sight (LOS) range, non-line-of-sight (NLOS) detection and degrades radar imaging. In this thesis, two levels of improvement are proposed and demonstrated. Firstly, an MMIC design is presented at the chip-level to achieve higher peak power directly from the chip. Secondly, novel beamforming techniques are proposed, which superimpose transmitted pulses spatially to produce strong radiating beams. Finally, the proposed beamforming networks are optimized and prototyped. The generation of the IR-UWB pulse is carried out through two successive stages on the MMIC, called as the impulse generator and the pulse former. The impulse generator generates a 7V sub-nanosecond voltage pulse, which is being used as an input to the pulse former stage. The pulse former performs the signal scaling, time-shifting, amplitude-reversal, and signal-addition to produce the desired Gaussian-enveloped multi-cycle IR-UWB pulse. The systematic circuit analysis is performed, and the effect of coupling capacitors on the amplification factor as well as impedance profile at each stage of pulse former are discussed in detail. In addition to this, the effect of temperature-dependent parasitic on the transient behaviour of the proposed IR-UWB pulse generator is analyzed, and the required mathematical model is derived. The proposed circuit is optimized for the highest possible output peak-power in the 3-5 GHz UWB band. The presented design is fully utilizing the existing 2 µm GaAs HBT cascode pair configuration, which significantly increases the output voltage swing while reducing the total power consumption. The measured output pulse has a peak-to-peak voltage of 10.2 V for a 50 Ω load. The proposed pulse generator MMIC has a total power consumption of 122 µW at 100 kHz pulse repetition frequency and power efficiency of 9.8% (18.4%). In order to further improve the peak power level in desired directions, the beam-pattern analysis of an electronically steerable multi-beam IR-UWB transmitter tag suited for real-time positioning systems is presented and demonstrated. Two linear arrays of four elements with an inter-element spacing of 18 cm and 10.2 cm are proposed and optimized. The array with a spacing of 10.2 cm is intentionally configured to produce orthogonal beams, which eventually provides better geometric dilution of precision (GDOP). The beam steering-angle analysis and an intensity table for the Gaussian-modulated multi-cycle IR-UWB beamforming array are provided. The proposed beamforming transmitter arrays are observed to achieve the scanning range from –60⁰ (–90⁰) to +60⁰ (+90⁰) with a scanning resolution of 5⁰ and 8⁰ in the measurements. In addition to this, a novel algorithm for the separation between distributed wireless sensor nodes of the virtual non-linear array is proposed for collaborative beamforming in the wireless sensor network system. The proposed algorithm can produce a single beam radiation pattern of the collaborative virtual radar array. The presented radiation pattern is proposed for Gaussian-shaped multi-cycle IR-UWB beamforming, which effectively reduces the grating lobes despite electrically large separation between the transmitting nodes. A random error of positioning for sensor nodes and random jitter for different IR-UWB pulse is incorporated in the analysis, and related simulation results are provided. A prototype for the time domain beam-pattern measurement is developed for proof-of-concept. The measurement results show better than 6dB suppression for side lobes radiation.

This paper proposes a method for mitigation of non-line-of-sight (NLOS) situations in a real time location system (RTLS) using an impulse radio ultra wide band (IR-UWB). Based on our experiment, we found that there is a slight chance to meet the line-of-sight (LOS) at all the readers of RTLS in a realistic scenario. In the NLOS environment, there are two problems of packet-miss error and multi-path error as well. To compensate for the packet-miss error, this paper presents a new algorithm (PPTi), which uses previous time information before the time difference of arrival (TDOA) positioning technique calculates the coordinate of the target. We also employed the Kalman Filter (KF) to mitigate multi-path error. Our proposed algorithm provides a 5.9% increased positioning success rate and a 25.6% decreased root mean square error (RMSE) in an NLOS environment.

Wireless Sensor Network (WSN) have been attracting increasing interest for supporting a new generation of ubiquitous computing systems with great potential for many applications. However, the communication paradigms in WSNs differ from the ones associated to traditional wireless networks, triggering the need for efficient wireless communication technology. Several wireless technologies have emerged ranging from short and medium distance. Bluetooth, ZigBee and Impulse Radio Ultra Wide Band (IR-UWB) are three popular short range wireless communications. Due to its various features and advantages (especially low power consumption and low complexity), IR-UWB is a very promising wireless communication technology for WSN. In this paper, we evaluate the main features and advantages of this new technology (IR-UWB) for WSN in terms of transmission time, data coding and power consumption compared to Bluetooth and ZigBee. To analyze and evaluate the main features and advantages of IR-UWB as an efficient short range wireless communication technology for WSN, we used MiXiM platform under OMNet++ simulator.

At present, location technology divides into outdoor location technology and indoor location technology. Comparing with other indoor location methods, ultra-wide band (UWB)indoor location technology has the advantages of strong anti-multipath interference ability and signal penetration ability. But, when this method faces large obstacles or metal obstacles, non line of sight (NLOS) will still occur. Indoor location system is a part of our project Home Care System for The Elderly. The NLOS of Indoor location system reduces the reliability of Home Care System for The Elderly. In order to improve the accuracy of location and efficiency of operation, an NLOS detection method based on k-nearest neighbors (KNN) algorithm is proposed. This algorithm modeled the training samples to find the K value with the highest recognition accuracy. The experimental results show that The NLOS detection accuracy of this method is 78% in the simulated apartment scene. With the same number of samples, the accuracy of the widely used Convolutional Neural Networks (CNN) algorithm is 67%. The experimental results show that KNN algorithm is more suitable for Home Care System for The Elderly for it can keep high accuracy with less requirement for the number of samples than CNN.

In recent years, indoor and outdoor positioning technology for the blind has attracted much more attention. The outdoor positioning technology has relatively matured. However, three-dimensional indoor positioning technology is facing many problems. Due to low positioning accuracy as well as slow positioning speed, there is no ideal implementation system at present. Light Fidelity (LiFi) technology is a new wireless transmission technology that uses the visible light spectrum, such as the light emitted by a light bulb, to transmit data. It transmits signals through the changing light of LED lights. When LED lights are properly laid out in the building, not only the function of lighting but also that of transmitting information are met at the same time. It is a good way to solve indoor positioning problems. This article studies an indoor positioning glasses for blind based on the LiFi technology. Different from other indoor positioning technologies such as ultrasound and wireless fidelity (WiFi), the design of indoor positioning glasses for the blind will propose new ideas of three-dimensional indoor positioning problems for the blind.

Recently ultra wideband impulse radio (UWB-IR) has been attracted much attention on short-range wireless communication, because UWB-IR has abilities to achieve high transmission rate, low power consumption and so on. Considering access-point (AP) terminal pair, as the transmission power of AP is limited to −41.3dBm/MHz from FCC regulation, result in low received signal intensity, thus time-reversal (TiR) scheme based on pre-rake combine technique is suggested as a promising solution to improve Eb/N0 of terminal and also keep terminal structure simple. In our previous work, it has been experimentally discussed that longer TiR filter length (number of combined multi-path) takes better Eb/N0 [1]. However when in high transmission rate, the longer filter length should also take the harder inter-symbol interference (ISI) resulting in degradation of bit error rate (BER). In this work under many kinds of transmission rates, the optimum TiR filter length has been discussed by measurement and simulation.

Based on impulse radio ultra wide band (IR-UWB) technology, the measuring and positioning of moving array shape are discussed. Because there are no conditions of fixed receivers and clock synchronization in real outdoor or field surroundings, only choice is unusual asynchronous measurement method, therefore, the scheme of measuring and processing must be changed, though the current TOA (Time Of Arrival) method is used. The array shape and positions of moving objects are both required in the most situations. The direct approach is to increase the number of measuring point, and the positioning problem would be resolved by triangular surveying method. The solution is generic at first sight, but its sensitivity to time-of-arrival accuracy imposes the choice of impulse radio ultra wide band hard ware and soft ware in the very context. The algorithm scheme mitigates the impact of non-line of sight ranging errors on positioning accuracy without any additional protocol hook. More particularly, the realistic IR-UWB ranging error models we use take into account UWB channel effects, as well as relative clock drifts. By error analyzing and simulation under the proper operation model, results are provided to illustrate the relevance of such a solution.

Location-awareness is becoming increasingly important in wireless networks. Indoor localization can be enabled through wideband or ultra-wide bandwidth (UWB) transmission, due to its fine delay resolution and obstacle-penetration capabilities. A major hurdle is the presence of obstacles that block the line-of-sight (LOS) path between devices, affecting ranging performance and, in turn, localization accuracy. Many techniques have been proposed to address this issue, most of which make modifications to the localization algorithm. Since many localization algorithms work with distance or angle estimates, rather than received waveforms, information inherent in the wideband waveform is lost, leading to sub-optimal ranging error mitigation. To avoid this information loss, we present a novel approach to mitigate ranging errors directly in the physical layer. In contrast to existing techniques, which detect the non-line-of-sight (NLOS) condition, our approach directly mitigates the bias incurred in both LOS and non-LOS conditions. In particular, we apply two classes of non-parametric regressors to form an estimate of the ranging error. Our work is based on, and validated by, an extensive indoor measurement campaign with FCC-compliant UWB radios. The results show that the proposed regressors provide significant performance improvements in various practical localization scenarios, compared to conventional approaches.

A 4 GS/s 2-bit non-time-interleaved flash ADC is designed for an IR-UWB (Impulse Radio Ultra Wide Band) receiver. In this flash ADC, implementing differential low-swing operation in analog part and CML (current mode logic) in digital part result in high-speed and low power consumption. Furthermore, because of the low-bit-sampling characteristic of the IR-UWB system, non-time-interleaved structure is used without digital calibration which largely saves the power consumption, chip area and cost. And a differential resistive reference ladder is designed to minimize the inaccuracy of the reference voltage. The proposed ADC dissipates 34 mW power from a 1.8 V supply while operating at 4 GHz. This chip has been fabricated in 0.18 μm 1P6M CMOS process and the ADC achieves 1.86-bit effective number of bits (ENOB) for input signal of 1 GHz at 4 GS/s in simulation of FFT analysis.

Understanding the indoor whereabouts of individuals and objects is important, especially for those who fall within the 71% of visually impaired individuals with a school education, students in 450 special education units and many other areas and aspects in Sri Lanka. Researchers have declared that, there isn’t any particularly good localization system, and the performance should be evaluated considering the approach and application. The most well-known indoor positioning (IP) technologies that have been historically deployed are Bluetooth, Wi-Fi, RFID (radio frequency identification), IR (Infrared), and UV (ultraviolet) whereas received signal strength (RSSI), fingerprinting, and triangulation methods have been used as common IP techniques. The combination of both IP technologies and techniques creates an IP system, and the integration of machine learning and IoT with the structured system essentially delivers an accurate and more advanced system. This paper contains a detailed, analytical review of a developed indoor positioning system derived from the existing indoor localization techniques, localization technologies, localization systems, algorithms, and performance matrixes. This also provides a comprehensive comparison between numerous existing systems to justify the proposed solution. This project has been developed to achieve better accuracy through low-cost deployment as an effective system to fill the gap in the scarcity of positioning systems in the world. This paper presents a descriptive introduction and problem definition, a critical discussion of results, machine learning models, benefits of the project, and future works. As later justified, ESP32 microcontroller and BLE beacons are utilized with RSSI fingerprinting method to develop this IP system and, as a part of the project, two data visualization methods have been introduced here using NodeRED dashboard and LC display. Overall, this project was developed with an effective combination of RSSI fingerprinting, IoT protocols, machine learning, and data interpretation methods. KEYWORDS: Indoor positioning, RSSI, Fingerprinting, Machine Learning, MQTT, ESP32, BLE beacons, NodeRED

High-precision indoor localization and tracking are essential requirements for the safe navigation and task execution of autonomous mobile robots. Despite the growing importance of mobile robots in various areas, achieving precise indoor localization remains challenging due to signal interference, multipath propagation, and complex indoor layouts. In this work, we present the first comprehensive study comparing the accuracy of Bluetooth low energy (BLE), WiFi, and ultra wideband (UWB) technologies for the indoor localization of mobile robots under various circumstances. In the performed experiments, the error margin of the WiFi-based systems reached 608.7 cm, which is not tolerable for most applications. As a commonly used technology in the existing tracking systems, the accuracy of BLE-based systems is at least 44.12% better than that of WiFi-based systems. The error margin of the BLE-based system in tracking static and mobile robots was 191.7 cm and 340.1 cm, respectively. The experiments showed that even with a limited number of UWB anchors, the system provides acceptable accuracy for tracking the mobile robots. Using only four UWB beacons in an environment of about 431 m2 area, the maximum error margin of detected positions by the UWB-based tracking system remained below 13.1 cm and 28.9 cm on average for the static and mobile robots, respectively. This error margin is 88.05% lower than that of the BLE-based system and 93.27% lower than that of the WiFi-based system on average. The high tracking precision, the need for a lower number of anchors, and the decreasing hardware costs point out that UWB will be the dominating technology in indoor tracking systems in the near future.

With the increasing demand for location-based services, indoor localization technology based on wireless sensor networks (WSNs) has recently received significant attention. Bluetooth low energy (BLE) has become a research hotspot among the numerous WSNs due to its ubiquitous deployment, low-power consumption, and low cost. Many previous BLE-based indoor localization technologies can only use received signal strength indication (RSSI) for localization in the 2-D plane and achieve coarse accuracy. However, high-accuracy location information is required in an increasing number of applications, e.g., elderly fall detection for medical applications, which urgently requires a new BLE-based localization technology in 3-D space. To this end, we propose Spotlight, an angle-based fine-grained indoor localization system in 3-D space using BLE sensors. The critical idea of the Spotlight is to measure the angle-of-arrival (AoA) and elevation-of-angle (EoA) of the signal from the target to the BLE receivers and utilize them to achieve accurate 3-D localization. Specifically, we develop an offset elimination algorithm and data stitching algorithm, utilizing the second-order cone (SoC) programming to obtain accurate angle estimates. Then, the simulated annealing algorithm (SAA) is used to search for the target location in 3-D space. Finally, we develop the prototype system with commercial off-the-shelf (COTS) BLE sensors and conduct extensive experiment measurements in real-world scenarios. The results demonstrate that the proposed system can achieve a median localization error of 36 cm in the 2-D plane and 48 cm in the 3-D space.

Wireless capsule endoscopy (WCE) presents many advantages over traditional wired endoscopic methods. The performance of WCE devices can be improved using high-frequency communication systems such as Impulse Radio-Ultra-Wideband (IR-UWB) to enable a high data rate transmission with low-power consumption. This paper presents the hardware implementation and experimental evaluation of a WCE device that uses IR-UWB signals in the frequency range of 3.5 GHz to 4.5 GHz to transmit image data from inside the body to a receiver placed outside the body. Key components of the IR-UWB transmitter, such as the narrow pulse generator and up-conversion based RF section are described in detail. This design employs a narrowband receiver in the WCE device to receive a control signal externally in order to control and improve the data transmission from the device in the body. The design and performance of a wideband implantable antenna that operates in the aforementioned frequency range is also described. The operation of the WCE device is demonstrated through a proof-of-concept experiment using meat.

An indoor positioning system (IPS) is a technology employed to locate objects and people within a building scenario using signal processing or other sensory information. Ultra Wide Band (UWB) is a versatile wireless technology that can be employed as an IPS and has shown very good performances. UWB can be used in many scenarios and its effectiveness in through wall detection along with its excellent resolution for person localization is one of the best applications of Impulse Radio (IR) UWB. The main objective of this work is to propose a concept for intelligent radar systems employing UWB augmented by machine learning approaches to not only localize but understand the location of a person or target within a building. Although suitably developed UWB is excellent for obtaining localizing data it does not automatically understand what that location effectively means or where it is thus further methods are required to create meaningful data for end user appreciation. Learning from the huge amount of UWB signal data through Multi Class Support Vector Machine (MC-SVM) architecture enables a truly evolving scheme to both localize targets and identify them in a useful way. Statistical analysis of the experimental results supports the proposed algorithm.