Receiver Module Research Articles

THE DEVELOPMENT AND VALIDATION OF A TACTICAL GRADE EGI SYSTEM FOR LAND VEHICULAR NAVIGATION APPLICATIONS

Abstract. Over recent years, the utilization of commercially available integrated navigation systems for the development of navigation algorithms has become increasingly commonplace. Nevertheless, the wide range of sensor quality on the market complicates system customization and restricts the evolution of navigation algorithms. This study aims to address these issues by creating an affordable, tactical-grade, real-time integrated navigation system, EGI-500 (Embedded GNSS and INS), encompassing both hardware and software components. EGI-500 incorporates a tactical-grade IMU500 and a Septentrio Mosaic-X5 GNSS receiver module. The integration process is segmented into three distinct stages. The first involves hardware integration, with an illustrative architecture diagram of the real-time navigation system. Second, we focus on data preprocessing, where a cross-correlation approach is proposed to tackle multi-sensor time synchronization issues, specifically to determine potential time lags in IMU data. The final phase covers the fusion of multi-sensor data and motion constraints. The Extended Kalman Filter (EKF) forms the backbone of this part, with Zero Velocity Update (ZUPT) and Non-Holonomic Constraints (NHC) being integrated into the Loosely Coupled (LC) scheme. Furthermore, the IMU calibration process is performed to ascertain necessary algorithmic parameters. Experimental results, conducted in diverse environments (open sky, GNSS challenging, and GNSS denied), will be presented in this paper. Comparisons with reference data indicate that the navigation accuracy of the developed integrated system, both in terms of hardware and navigation algorithm, achieves expected meter-level accuracy, fulfilling the "Which Lane" and "Which Road" level criteria in varied environments. Furthermore, outcomes from the GNSS denied environment align with predictions based on propagation error theory, demonstrating the feasibility of our navigation algorithm for tactical integrated navigation systems.

Closed Solar Thermal Receiver for Air at Ambient Pressure

The concept for a closed solar thermal receiver for air at ambient pressure integrates robust heat storage with solids for concentrated solar power plants. The scalable modular receiver design features large internal surface areas for an efficient heat transfer and provides cavity effects to recover externally reflected radiation and heat. A competitive thermal efficiency was preliminarily calculated for the receiver design. The simulations of receivers with 2 MW and 150 MW thermal output indicate that the velocities of the heat transfer fluid and the temperatures of the receiver components remain in manageable magnitudes. The manufacturability of a fine cooling structure with thousands of cooling pins inside the ceramic receiver cap is demonstrated. Black coating of the outer receiver cap surface significantly increases the absorption of solar radiation. First tests for a single receiver module indicate feasibility of the concept. Further tests will be carried out and a pilot plant is to be prepared.

Time course from cochlear implant surgery to non-use for congenitally deaf recipients implanted as children over ten years ago.

To determine the time-course from first cochlear implantation to non-use, to characterise non-users' receptive and expressive communication, and document known risk factors for inconsistent use, for congenitally deaf non-users of cochlear implants implanted as children at least ten years ago. Retrospective service evaluation. All congenitally deaf patients who received a first cochlear implant as children at least ten years ago at a regional service, and were currently non-users, were identified. They were characterised in terms of ages at implantation and non-use, known risk factors for inconsistent CI use or CI non-use, and outcome measures were the Meaningful Auditory Integration Scale (MAIS) and Meaningful Use of Speech Scale (MUSS) scores. Seventeen patients met the inclusion criteria. They were implanted from 1990 to 2006. Median age at implantation was 4 years (range: 2-11), median age at non-use was 17 years (range: 9-31), and median duration of use was 8.5 years (range: 4-25). All used sign or gesture as their primary expressive and receptive communication modes. In addition, each child had at least one other known risk factor for inconsistent CI use. At 3 years post-implantation, mean Parent-rated MAIS scores were 76.5% (N = 14), and mean MUSS scores were 43.1% (N = 9). This cohort included cases where CI use was rejected following longer periods of time than previously reported, highlighting a need for long-term support, particularly around the ages of life transitions. Studies conducted when the earliest cohort of paediatric CI users were younger, and studies reliant on parent or patient reports, may under-estimate long-term non-use rates. No non-users were identified among congenitally-deaf children implanted 10-15 years ago. Further research is warranted to explore relationships between risk factors, including communication mode, and non-use to inform expectation setting and candidacy selection.

MFD-Net: Modality Fusion Diffractive Network for Segmentation of Multimodal Brain Tumor Image.

Automatic brain tumor segmentation using multi-parametric magnetic resonance imaging (mpMRI) holds substantial importance for brain diagnosis, monitoring, and therapeutic strategy planning. Given the constraints inherent to manual segmentation, adopting deep learning networks for accomplishing accurate and automated segmentation emerges as an essential advancement. In this article, we propose a modality fusion diffractive network (MFD-Net) composed of diffractive blocks and modality feature extractors for the automatic and accurate segmentation of brain tumors. The diffractive block, designed based on Fraunhofer's single-slit diffraction principle, emphasizes neighboring high-confidence feature points and suppresses low-quality or isolated feature points, enhancing the interrelation of features. Adopting a global passive reception mode overcomes the issue of fixed receptive fields. Through a self-supervised approach, the modality feature extractor effectively utilizes the inherent generalization information of each modality, enabling the main segmentation branch to focus more on multimodal fusion feature information. We apply the diffractive block on nn-UNet in the MICCAI BraTS 2022 challenge, ranked first in the pediatric population data and third in the BraTS continuous evaluation data, proving the superior generalizability of our network. We also train separately on the BraTS 2018, 2019, and 2021 datasets. Experiments demonstrate that the proposed network outperforms state-of-the-art methods.

Ultrasonic lamination defects detection of carbon fiber composite plates based on multilevel LSTM

During the production of carbon fiber composites (CFC), various forming methods and complex processes can introduce different types of defects, with lamination defects being a major concern. In this paper, we propose a multilevel Long Short-Term Memory (LSTM) neural network combined with ultrasonic detection to identify the lamination defects in carbon fiber composites. Unlike conventional ultrasonic detection that requires multiple sets of probes, this method only employs a one-to-one transmission and reception mode. The COMSOL-Multiphysics finite element software is utilized to simulate the ultrasonic transmission and generate the necessary ultrasonic data. By incorporating multiple levels of learning, the accuracy and convergence of the traditional LSTM can be obviously enhanced. This approach uses ultrasound waveform data collected from a single set of probes to predict the locations and sizes of lamination defects. Based on fewer than 10,000 datasets where each dataset represents a waveform, the numerical results demonstrate a prediction accuracy of over 90% for defect position and size. Moreover, the multilevel LSTM method exhibits convergence, and incorporating more data can further promote the prediction accuracy. This method offers a time-saving, labor-saving, and cost-effective solution for detecting and analyzing defects in CFC.

10‐GHz band 2 × 2 phased‐array radio frequency receiver with 8‐bit linear phase control and 15‐dB gain control range using 65‐nm complementary metal–oxide–semiconductor technology

AbstractWe propose a 10‐GHz 2 × 2 phased‐array radio frequency (RF) receiver with an 8‐bit linear phase and 15‐dB gain control range using 65‐nm complementary metal–oxide–semiconductor technology. An 8 × 8 phased‐array receiver module is implemented using 16 2 × 2 RF phased‐array integrated circuits. The receiver chip has four single‐to‐differential low‐noise amplifier and gain‐controlled phase‐shifter (GCPS) channels, four channel combiners, and a 50‐Ω driver. Using a novel complementary bias technique in a phase‐shifting core circuit and an equivalent resistance‐controlled resistor–inductor–capacitor load, the GCPS based on vector–sum structure increases the phase resolution with weighting‐factor controllability, enabling the vector–sum phase‐shifting circuit to require a low current and small area due to its small 1.2‐V supply. The 2 × 2 phased‐array RF receiver chip has a power gain of 21 dB per channel and a 5.7‐dB maximum single‐channel noise‐figure gain. The chip shows 8‐bit phase states with a 2.39° root mean‐square (RMS) phase error and a 0.4‐dB RMS gain error with a 15‐dB gain control range for a 2.5° RMS phase error over the 10 to10.5‐GHz band.

Model-Based Deep Learning Receiver Design for Rate-Splitting Multiple Access

Effective and adaptive interference management is required in next generation wireless communication systems. To address this challenge, Rate-Splitting Multiple Access (RSMA), relying on multi-antenna rate-splitting (RS) at the transmitter and successive interference cancellation (SIC) at the receivers, has been intensively studied in recent years, albeit mostly under the assumption of perfect Channel State Information at the Receiver (CSIR) and ideal capacity-achieving modulation and coding schemes. To assess its practical performance, benefits, and limits under more realistic conditions, this work proposes a novel design for a practical RSMA receiver based on model-based deep learning (MBDL) methods, which aims to unite the simple structure of the conventional SIC receiver and the robustness and model agnosticism of deep learning techniques. The MBDL receiver is evaluated in terms of uncoded Symbol Error Rate (SER), throughput performance through Link-Level Simulations (LLS), and average training overhead. Also, a comparison with the SIC receiver, with perfect and imperfect CSIR, is given. Results reveal that the MBDL receiver outperforms by a significant margin the SIC receiver with imperfect CSIR, due to its ability to generate on demand non-linear symbol detection boundaries in a pure data-driven manner.

Wireless Animatronic Hand

As a result of employees utilizing their bare hands, there are more accidents in industries every year. Animatronic hands resemble human hands and are capable of carrying out a variety of tasks that humans are unable to do. Human hands cannot readily finish difficult tasks, but animatronic hands can mimic human movements and complete them. A number of actuators and sensors make up the robotic hand, which are managed by a person's hand. The pushers control how far the fingers can move. We employ flex sensors to detect the positions. The positions and motion of the hand are reported by sensors to Arduino. The microcontroller uses a 433MHz transmitter and receiver in both transmitter and receiver side to used for transmitting the data, so it will be access in remote area. We employ servo motors as actuators by getting the position and motion from another microcontroller also attached. Two microcontrollers are interconnected with 433MHz transmitter and receiver, Transmitter and receiver for 433 MHz When sending and receiving radio signals between any two devices, RF refers to a set of electronic RF transmitters and receiver modules. The transmitter module at the transmitter end transmits the data, which the receiver module at the receiver end receives.

Boat Tracking, Weather Monitoring and Ocean Cleaning System Based on IoT

Sea cleaning is challenging these days, so humans invented a method to organically clean the sea or any other bodies of water utilising smart technology with the aid of hub MCU and Internet of Things (IoT) stage. This paper suggests developing a system that uses both a tracking unit and a monitoring unit independently to clear ocean garbage easily, monitor the weather, and detect border crossings. An Arduino Uno (microcontroller) with an ATmega328p chip is used to collect and change sensor data. The IR sensor and DHY11 sensor are the sensors used in the microcontroller. A NEO-6M GPS receiver module and Bluetooth module are used to locate the boat. The Global Positioning System (GPS) location is collected and uploaded to the IoT cloud via a wifi module. The system’s microprocessor instructs the buzzer to sound. In order to communicate with the base station, which keeps tabs on the boats at sea, it also uses a message transmitter. The suggested system alerts both the coast guards and fishermen.

Design of Nonreciprocal Filtering Antenna Using Spatio-Temporal Modulated SIW Resonators

This article reports on, for the first time, the design of nonreciprocal filtering antennas using spatio-temporal modulated substrate integrated waveguide (SIW) resonators. It consists of two SIW cavities and a half-mode SIW (HMSIW) cavity, which is designed as the last-stage resonator and the radiator. By integrating time-modulated capacitors on the surface gaps of the three cavities, the nonreciprocal radiation patterns in transmission and reception modes are achieved at the same operating frequency. Three radiation nulls are generated due to the cross-coupling in the time-modulated network and source-load coupling. The theoretical analysis of the co-designed nonreciprocal SIW filtering antenna is detailed, along with methods for its co-simulations and measurements. For the proof-of-concept demonstration, a nonreciprocal SIW filtering antenna operating at 2.4 GHz is designed and fabricated. The measured 10-dB bandwidth and peak gain are 1.7% and 2.6 dBi, respectively. The measured realized gains at transmission and reception show that the reverse isolation is greater than 11 dB within a bandwidth of 30 MHz. The frequency selectivity values are 756 and 368 dB/GHz at the left and right sides of the passband, respectively.

Design and modelling of modulated cw laser generation in lidar application

In this work, we designed a configuration that may be used for direct detection of light, detection and ranging sensing method based on generated continuous wave laser and characterized by range measurements. The generation of modulated laser distance is studied and analysed by several distances where modulation of laser signal is utilized. The modelling configuration consisted of transmission module that comprises of signal generator, modulator, and propagation module, object target, and receiver modules comprises of photodetector, amplifier, filter, and visualizers. The design and configuration were developed by Optisystem layout, and the study and analysis are done by simulation using the developed model. A subsystem of range measurement was designed to detect varied distances of detection of target object by the generated modulation of continuous wave laser at 10, 50, 100 and 200 meters respectively. The results discussed were based on the power received and frequency given by different detection ranges. Analysis shows that the detection scheme is sensitive to the received electromagnetic radiation and the signal is better at shorter haul based on the generated modulation of the continuous wave source and the signal deteriorated as target distance is increased.

Frizzled2 receives WntA signaling during butterfly wing pattern formation.

Butterfly color patterns provide visible and biodiverse phenotypic readouts of the patterning processes. Although the secreted ligand WntA has been shown to instruct the color pattern formation in butterflies, its mode of reception remains elusive. Butterfly genomes encode four homologs of the Frizzled-family of Wnt receptors. Here, we show that CRISPR mosaic knockouts of frizzled2 (fz2) phenocopy the color pattern effects of WntA loss of function in multiple nymphalids. Whereas WntA mosaic clones result in intermediate patterns of reduced size, fz2 clones are cell-autonomous, consistent with a morphogen function. Shifts in expression of WntA and fz2 in WntA crispant pupae show that they are under positive and negative feedback, respectively. Fz1 is required for Wnt-independent planar cell polarity in the wing epithelium. Fz3 and Fz4 show phenotypes consistent with Wnt competitive-antagonist functions in vein formation (Fz3 and Fz4), wing margin specification (Fz3), and color patterning in the Discalis and Marginal Band Systems (Fz4). Overall, these data show that the WntA/Frizzled2 morphogen-receptor pair forms a signaling axis that instructs butterfly color patterning and shed light on the functional diversity of insect Frizzled receptors.

Design Validation and Reliability Assurance of Electronic Systems Using the Next Generation RGT Models

Arrhenius Accelerated Growth Model (AAGT) is the next generation accelerated testing models used for design validation and reliability assurance of electronics systems. These models are used in design and manufacturing phases towards reliability enhancement of the system respectively. AAGT Models uses Highly Accelerated Stresses for screening of the components towards uncovering Compared to traditional qualification test methods, design flaws, latent defects, component selection problems, and manufacturing flaws can be detected fast. The procedure includes thermal dwells and quick temperature changes while subjecting the test unit to increasing degrees of stress. Dynamic stresses (Pseudo-Random Vibration covering all 6DOF systems) and a combination of thermal and dynamic PSD stresses towards quickly precipitating inherent/hidden defects quickly. These Accelerated models used to qualify modern active array radar modules like Transmit Receive Modules (TRMs) which will be in large numbers and It will be difficult and time-consuming to filter these modules individually using the traditional way. To increase the quality and dependability of electronic devices, much accelerated life tests have been extensively adopted. However, extremely accelerated life tests may only be used as a qualitative approach to assess a product's dependability; they cannot be used to quantify a product's reliability, such as MTBF/MTTF. Consequently, in order to efficiently assess the level of product reliability while improving product reliability in a timely manner. HALT/HASS uses Arrhenius Accelerated Growth Model that is an effective technique used for screening of the module with in short period. This paper discuss in detail with a case study on active array modules deliberating about the test methodology, challenges faced during Using Arrhenius accelerated test models, rapid testing and assessment of these Four channel TRMs used for airborne Fire Control Radar for combat operations.

Child drowning prevention: GPS and LoRa based emergency alert system

UNICEF recently published in the "Country Office Report 2021" about the mortality of children in Bangladesh, "Every day, 30 children die from drowning – Bangladesh's second leading cause of under-five mortality. Drowning is preventable, and most cases occur within a child's home community." Bangladesh is a country of rivers, which means Bangladesh called a riverine country located in South Asia. The Center for Injury Prevention and Research conducted a survey, Around 19000 people of (all types of ages) drown every year in Bangladesh. Among them, 14500 which mean 77% are children. In our research, the emergency alert system is designed to be cost-effective and user-friendly for village communities in Bangladesh. The system is divided into two components: the kid is equipped with the transmitter, and the receiver is placed at home. The transmitter and receiver both use a LoRa transmission module that can communicate accurately within a 300-meter range (coverage up to 10 Kilometers) and can transmit 256 bytes of data. The transmitter collects geolocation data using a GPS module and sends the data to the receiver using the LoRa module. The receiver module is configured by setting up the geolocation of risky places. The receiver will send SMS or buzzing the receiver to alert the parents when the transmitter or kid is nearby risky places. The Equirectangular approximation method calculates the distance between children's positions from risky areas. Additionally, the transmitter and receiver may communicate encrypted messages using AES 128-bit symmetric encryption technology compatible with Arduino Nano controller. Thus, our emergency alert system can save children from drowning in the home environment.

The light source of the TRIDENT pathfinder experiment

In September 2021, a site scouting mission known as the TRIDENT pathfinder experiment (TRIDENT EXplorer, T-REX for short) was conducted in the South China Sea with the goal of envisaging a next-generation multi-cubic-kilometer neutrino telescope. One of the main tasks is to measure the in-situ optical properties of seawater at depths between 2800 m and 3500 m, where the neutrino telescope will be instrumented. To achieve this, we have developed a light emitter module equipped with a clock synchronization system to serve as the light source, which could be operated in pulsing and steady modes. Two light receiver modules housing both photomultiplier tubes (PMTs) and cameras are employed to detect the photons emitted by the light source. This paper presents the instrumentation of the light source in T-REX, including its design, calibration, and performance.

Distributed Batteryless Access Control for Data and Energy Integrated Networks: Modeling and Performance Analysis

Radio-frequency (RF) signals are capable of simultaneously transferring data and energy from a hybrid access point (HAP) toward battery-powered and batteryless wireless devices. Battery-powered and batteryless wireless devices with the capability of RF energy harvesting need a distributed access control protocol with collision avoidance to achieve higher energy efficiency. We study the performance of a data and energy integrated network (DEIN) that adopts an enhanced carrier sensing multiple access with collision avoidance (CSMA/CA) protocol. Each device in this network can switch to RF energy harvesting mode or data reception mode according to HAP’s instruction, and freezes its backoff counter when energy storage is insufficient. By invoking a three-dimensional (3D) Markov chain, we model the operating behaviors of batteryless wireless devices and an HAP in a DEIN. Apart from backoff operations of devices, the 3D Markov chain also depicts their dynamic energy changes, including RF energy harvesting and energy consumption. Wireless devices consume energy harvested from the HAP’s downlink transmissions for powering their data upload and random backoff. With the aid of the 3D Markov chain, the upload throughput of devices can be obtained in semi-closed-form. Moreover, a decoupling method is proposed to approximate throughput performance with low complexity. The accuracy of our theoretical model is validated by simulation results. By characterizing the impact of various parameters on throughput performance, a design guideline for a DEIN with a distributed batteryless access protocol is provided.

Ocean Turbulence Observation Techniques and Data Processing Algorithms based on SAR Sequence Images

Waves in the ocean are a widespread phenomenon and their effective detection requires the use of high-resolution, large-area detection devices. Synthetic aperture radar (SAR), with its all-weather performance and high resolution, is often used for the detection and imaging of both land and ocean, as well as large-area, high-resolution SAR and interferometric SAR, which are all based on SAR enhancements. This has become an important area of research in marine sensors, and the use of multiple-input multiple-output (MIMO) reception modes for detection and imaging of large-area, high-resolution SAR data has become one of the research priorities for obtaining large-area, high-resolution SAR data. Oceanic internal waves generate internal mixing of seawater through unstable fragmentation, which is an important mechanism for maintaining the meridional overturning circulation within the ocean, and the strong currents and strong mixing processes generated by large amplitude internal waves carry enormous energy. The main objective of this paper is to investigate ocean turbulence observation techniques and data processing algorithms based on SAR sequence images. The research is of great significance for the development of marine science, and the technical areas studied are of great research significance for the development of the marine economy, breakthroughs in marine research technology, and the development of the marine industry.

A fast tunable driver of light source for the TRIDENT Pathfinder experiment

TRIDENT (The tRopIcal DEep-sea Neutrino Telescope) is a proposed next-generation neutrino telescope to be constructed in the South China Sea. In September 2021, the TRIDENT Pathfinder experiment (TRIDENT EXplorer, T-REX for short) was conducted to evaluate the in-situ optical properties of seawater. The T-REX experiment deployed three digital optical modules at a depth of 3420 meters, including a light emitter module (LEM) and two light receiver modules (LRMs) equipped with photomultiplier tubes (PMTs) and cameras to detect light signals. The LEM emits light in pulsing and steady modes. It features a fast tunable driver to activate light-emitting diodes (LEDs) that emit nanosecond-width light pulses with tunable intensity. The PMTs in the LRM receive single photo-electron (SPE) signals with an average photon number of approximately 0.3 per 1-microsecond time window, which is used to measure the arrival time distribution of the SPE signals. The fast tunable driver can be remotely controlled in real-time by the data acquisition system onboard the research vessel, allowing for convenient adjustments to the driver's parameters and facilitating the acquisition of high-quality experimental data. This paper describes the requirements, design scheme, and test results of the fast tunable driver, highlighting its successful implementation in the T-REX experiment and its potential for future deep-sea experiments.

Power efficient stochastic modeling for Narrowband Internet of Things devices in 5G networks

AbstractNarrowband Internet of Things (NB‐IoT) embodies the vision of connecting virtually anything with everything and aims to support a massive number of devices for small data transmission. However, an efficient power‐saving model for battery‐operated NB‐IoT devices is the need of the hour. In addition to the legacy discontinuous reception (DRX) scheme, efficient beamforming helps in saving device power. Moreover, the extended discontinuous reception (eDRX) mode and Power Saving Mode (PSM) in Radio Resource Control (RRC) idle mode enhances the effect of sleep while no data is available for the device to serve. In this work, power‐saving techniques for NB‐IoT devices are studied via stochastic modeling. This work proposes a semi‐Markov model (SMM) for beam measurement and beamforming‐based DRX mechanism, in RRC modes. The steady‐state probabilities for the SMM are calculated using the two‐stage method. The numerical results show the effective contribution of efficient beamforming, eDRX state and PSM state in enhancing the power saving of NB‐IoT devices.

A self-powered, high-precision and minimum-channel touch panel coupling triboelectrification and uniform resistance film

Touch panels utilizing surface-capacitive mechanism are ubiquitous in our daily life. However, the need for an additional probe signal generator and receiver module to detect the resistance distribution and variation caused by finger touching adds complexity and energy consumption to the system. Herein, we propose a self-powered and high-precision tribo-touch-position sensor (TPS) that can operate without an external probe signal generator and receiver module. By detecting the contact electrification signal and extracting the signal ratio between the edges of a uniform resistance film, TPS exhibits precise touch position detection with minimal channels. The mechanism and feasibility of this sensor is systematically analyzed from theory and experiment. Moreover, the resistance range and parameters that affect the sensing performance are discussed in depth. Compared to traditional capacitive touch panels, TPS can function in high moisture conditions and is not limited to grounded objects. Finally, the designed TPS achieves spatial resolutions of 0.001 and 1 mm in touching space and size, and a prototype 2D touch panel is fabricated experimentally. The signals ratio of 2D touch panel changes more obviously in the middle than on the sides while the fingers touch various positions. This work provides an alternative platform for simple and diverse contact localization using triboelectric effect.