An Adaptive RF Front-End Architecture for Multi-Band SDR in Avionics.

This study introduces a reconfigurable and agile RF front-end (RFFE) architecture that significantly enhances the performance of software-defined radios (SDRs) by seamlessly adjusting to varying signal requirements, frequencies, and protocols. This flexibility greatly enhances spectrum utilization, signal integrity, and overall system efficiency-critical factors in aviation, where reliable communication, navigation, and surveillance systems are vital for safety. A versatile RF front-end is thus indispensable, enhancing connectivity and safety standards.

Publish/Subscribe Method for Real-Time Data Processing in Massive IoT Leveraging Blockchain for Secured Storage.

In the Internet of Things (IoT) era, the surge in Machine-Type Devices (MTDs) has introduced Massive IoT (MIoT), opening new horizons in the world of connected devices. However, such proliferation presents challenges, especially in storing and analyzing massive, heterogeneous data streams in real time. In order to manage Massive IoT data streams, we utilize analytical database software such as Apache Druid version 28.

Real-Time Sensor-Embedded Neural Network for Human Activity Recognition.

This article introduces a novel approach to human activity recognition (HAR) by presenting a sensor that utilizes a real-time embedded neural network. The sensor incorporates a low-cost microcontroller and an inertial measurement unit (IMU), which is affixed to the subject's chest to capture their movements. Through the implementation of a convolutional neural network (CNN) on the microcontroller, the sensor is capable of detecting and predicting the wearer's activities in real-time, eliminating the need for external processing devices.

A Secure ZUPT-Aided Indoor Navigation System Using Blockchain in GNSS-Denied Environments.

This paper proposes a novel Blockchain-based indoor navigation system that combines a foot-mounted dual-inertial measurement unit (IMU) setup and a zero-velocity update (ZUPT) algorithm for secure and accurate indoor navigation in GNSS-denied environments. The system estimates the user's position and orientation by fusing the data from two IMUs using an extended Kalman filter (EKF). The ZUPT algorithm is employed to detect and correct the error introduced by sensor drift during zero-velocity intervals, thus enhancing the accuracy of the position estimate.

FPGA-Based Autonomous GPS-Disciplined Oscillatorsfor Wireless Sensor Network Nodes.

Numerous devices in distributed wireless sensor arrays require a high-accuracy timing reference. Although the GPS-disciplined oscillators have been developed for decades, the hardware design still has performance limitations. In this context, we present the hardware implementation for a GPS-disciplined oscillator with an automatic adaptive drift correction algorithm, which is implemented in a low-cost, high-speed field-programmable gate array (FPGA) device.

Landing System Development Based on Inverse Homography Range Camera Fusion (IHRCF).

The Unmanned Aerial Vehicle (UAV) is one of the most remarkable inventions of the last 100 years. Much research has been invested in the development of this flying robot. The landing system is one of the more challenging aspects of this system's development.

Applying a ToF/IMU-Based Multi-Sensor Fusion Architecture in Pedestrian Indoor Navigation Methods.

The advancement of indoor Inertial Navigation Systems (INS) based on the low-cost Inertial Measurement Units (IMU) has been long reviewed in the field of pedestrian localization. There are various sources of error in these systems which lead to unstable and unreliable positioning results, especially in long term performances. These inaccuracies are usually caused by imperfect system modeling, inappropriate sensor fusion models, heading drift, biases of IMUs, and calibration methods.

A New Perspective on Low-Cost MEMS-Based AHRS Determination.

Attitude and heading reference system (AHRS) is the term used to describe a rigid body's angular orientation in three-dimensional space. This paper describes an AHRS determination and control system developed for navigation systems by integrating gyroscopes, accelerometers, and magnetometers signals from low-cost MEMS-based sensors in a complementary adaptive Kalman filter. AHRS estimation based on the iterative Kalman filtering process is required to be initialized first.

Multi-Constellation Software-Defined Receiver for Doppler Positioning with LEO Satellites.

A Multi-Constellation Software-Defined Receiver (MC-SDR) is designed and implemented to extract the Doppler measurements of Low Earth Orbit (LEO) satellite's downlink signals, such as Orbcomm, Iridium-Next, Globalstar, Starlink, OneWeb, SpaceX, etc. The Doppler positioning methods, as one of the main localization algorithms, need a highly accurate receiver design to track the Doppler as a measurement for Extended Kalman Filter (EKF)-based positioning. In this paper, the designed receiver has been used to acquire and track the Doppler shifts of two different kinds of LEO constellations.

Accuracy Improvement of Attitude Determination Systems Using EKF-Based Error Prediction Filter and PI Controller.

Accurate attitude and heading reference system (AHRS) play an essential role in navigation applications and human body tracking systems. Using low-cost microelectromechanical system (MEMS) inertial sensors and having accurate orientation estimation, simultaneously, needs optimum orientation methods and algorithms. The error of attitude estimation may lead to imprecise navigation and motion capture results.

New Approach of High Sensitivity Techniques Using Collective Detection Method with Multiple GNSS Receivers.

The Collective Detection (CD) technique is a promising approach to meet the requirements for signal acquisition in GNSS-harsh environments. The CD approach has been proposed because of its potential to operate as both a direct positioning method and a high-sensitivity acquisition method. This paper is dedicated to the development of a new CD architecture for processing satellite signals in challenging environments.

Comparison of L1 and L5 Bands GNSS Signals Acquisition.

Nowadays, civil Global Navigation Satellite System (GNSS) signals are available in both L1 and L5 bands. A receiver does not need to acquire independently the signals in both bands coming from a same satellite, since their carrier Doppler and code delay are closely related. Therefore, the question of which one to acquire first rises naturally.

Satellite Launcher Navigation with One Versus Three IMUs: Sensor Positioning and Data Fusion Model Analysis.

Using multiple IMUs allows both their distribution along vehicle structures and a reliance on integration methods, which is not possible with a single IMU. This paper addresses the issue of relying on three IMUs instead of only one of a higher quality in the context of a satellite launcher. The impact of the IMU positions was tested by comparing collocated IMUs against IMUs installed in the head of each launcher stage.

Implementation Strategies for a Universal Acquisition and Tracking Channel Applied to Real GNSS Signals.

This paper presents a universal GNSS receiver channel capable of tracking any civil GNSS signal. This fundamentally differs from dedicated channels, each customized for a given signal. A mobile device could integrate fewer universal channels to harvest all available signals.

An Accurate and Fault-Tolerant Target Positioning System for Buildings Using Laser Rangefinders and Low-Cost MEMS-Based MARG Sensors.

Target positioning systems based on MEMS gyros and laser rangefinders (LRs) have extensive prospects due to their advantages of low cost, small size and easy realization. The target positioning accuracy is mainly determined by the LR's attitude derived by the gyros. However, the attitude error is large due to the inherent noises from isolated MEMS gyros.

Modification of an RBF ANN-Based Temperature Compensation Model of Interferometric Fiber Optical Gyroscopes.

This paper presents modification of Radial Basis Function Artificial Neural Network (RBF ANN)-based temperature compensation models for Interferometric Fiber Optical Gyroscopes (IFOGs). Based on the mathematical expression of IFOG output, three temperature relevant terms are extracted, which include: (1) temperature of fiber loops; (2) temperature variation of fiber loops; (3) temperature product term of fiber loops. Then, the input-modified RBF ANN-based temperature compensation scheme is established, in which temperature relevant terms are transferred to train the RBF ANN.

A novel optimal configuration form redundant MEMS inertial sensors based on the orthogonal rotation method.

In order to improve the accuracy and reliability of micro-electro mechanical systems (MEMS) navigation systems, an orthogonal rotation method-based nine-gyro redundant MEMS configuration is presented. By analyzing the accuracy and reliability characteristics of an inertial navigation system (INS), criteria for redundant configuration design are introduced. Then the orthogonal rotation configuration is formed through a two-rotation of a set of orthogonal inertial sensors around a space vector.