Browse Topic: Telecommunications
The rapid evolution of electric vehicles (EVs) necessitates advanced electronic control units (ECUs) for enhanced safety, monitoring, and performance. This study introduces an innovative ECU system designed with a modular architecture, incorporating real-time monitoring, cloud connectivity, and crash sensing. The methodology includes cost-effective design strategies, integrating STM32 controllers, CAN bus systems, and widely available sensors for motor RPM and temperature monitoring. Key findings demonstrate that the proposed ECU system improves data reliability, enhances vehicle safety through crash response systems, and enables predictive maintenance via cloud connectivity. This scalable and affordable ECU is adaptable to a broad range of EV models.
The U-Shift IV represents the latest evolution in modular urban mobility solutions, offering significant advancements over its predecessors. This innovative vehicle concept introduces a distinct separation between the drive module, known as the driveboard, and the transport capsules. The driveboard contains all the necessary components for autonomous driving, allowing it to operate independently. This separation not only enables versatile applications - such as easily swapping capsules for passenger or goods transportation - but also significantly improves the utilization of the driveboard. By allowing a single driveboard to be paired with different capsules, operational efficiency is maximized, enabling continuous deployment of driveboards while the individual capsules are in use. The primary focus of U-Shift IV was to obtain a permit for operating at the Federal Garden Show 2023. To achieve this goal, we built the vehicle around the specific requirements for semi-public road
This SAE Aerospace Recommended Practice (ARP) describes terminology specific to unmanned systems (UMSs) and definitions for those terms. It focuses only on terms used exclusively for the development, testing, and other activities regarding UMSs. It further focuses on the autonomy and performance measures aspects of UMSs and is based on the participants’ earlier work, the Autonomy Levels for Unmanned Systems (ALFUS) Framework, published as NIST Special Publication 1011-I-2.0 and NIST Special Publication 1011-II-1.0. This Practice also reflects the collaboration results with AIR5665. Terms that are used in the community but can be understood with common dictionary definitions are not included in this document. Further efforts to expand the scope of the terminology are being planned.
This article introduces a comprehensive cooperative navigation algorithm to improve vehicular system safety and efficiency. The algorithm employs surrogate optimization to prevent collisions with cooperative cruise control and lane-keeping functionalities. These strategies address real-world traffic challenges. The dynamic model supports precise prediction and optimization within the MPC framework, enabling effective real-time decision-making for collision avoidance. The critical component of the algorithm incorporates multiple parameters such as relative vehicle positions, velocities, and safety margins to ensure optimal and safe navigation. In the cybersecurity evaluation, the four scenarios explore the system’s response to different types of cyberattacks, including data manipulation, signal interference, and spoofing. These scenarios test the algorithm’s ability to detect and mitigate the effects of malicious disruptions. Evaluate how well the system can maintain stability and avoid
The global satellite communications (SATCOM) sector is undergoing profound transformation. Fueled by the rapid growth of low Earth-orbit (LEO) constellations, increased government investment, and heightened demand for secure, high-throughput connectivity, the market is projected to expand from $66.75 billion in 2025 to $103.78 billion by 20291, 2. This momentum reflects a broader realignment of priorities across commercial and defense markets: a shift from reliance on legacy geostationary systems toward agile, resilient networks capable of supporting next-generation missions and applications.
With 2D cameras and space robotics algorithms, astronautics engineers at Stanford have created a navigation system able to manage multiple satellites using visual data only. They recently tested it in space for the first time. Stanford University, Stanford, CA Someday, instead of large, expensive individual space satellites, teams of smaller satellites - known by scientists as a “swarm” - will work in collaboration, enabling greater accuracy, agility, and autonomy. Among the scientists working to make these teams a reality are researchers at Stanford University's Space Rendezvous Lab, who recently completed the first-ever in-orbit test of a prototype system able to navigate a swarm of satellites using only visual information shared through a wireless network. “It's a milestone paper and the culmination of 11 years of effort by my lab, which was founded with this goal of surpassing the current state of the art and practice in distributed autonomy in space,” said Simone D'Amico
In October 2024, Kongsberg NanoAvionics discovered damage to their MP42 satellite, and used the discovery as an opportunity to raise awareness on the need to reduce space debris generated by satellites. Kongsberg NanoAvionics, Vilnius, Lithuania Our MP42 satellite, which launched into low Earth orbit (LEO) two and a half years ago aboard the SpaceX Transporter-4 mission, recently took an unexpected hit from a small piece of space debris or micrometeoroid. The impact created a 6 mm hole, roughly the size of a chickpea, in one of its solar panels. Despite this damage, the satellite continued performing its mission without interruption, and we only discovered the impact thanks to an image taken by its onboard selfie camera in October of 2024. It is challenging to pinpoint exactly when the impact occurred because MP42's last selfie was taken a year and a half ago, in April of 2023.
Someday, instead of large, expensive individual space satellites, teams of smaller satellites – known by scientists as a “swarm” – will work in collaboration, enabling greater accuracy, agility, and autonomy. Among the scientists working to make these teams a reality are researchers at Stanford University’s Space Rendezvous Lab, who recently completed the first-ever in-orbit test of a prototype system able to navigate a swarm of satellites using only visual information shared through a wireless network.
The U.S. Naval Research Laboratory (NRL), in partnership with NASA’s Marshall Space Flight Center (MSFC), has developed StarBurst, a small satellite (SmallSat) instrument for NASA’s StarBurst Multimessenger Pioneer mission, which will detect the emission of short gamma-ray bursts (GRBs), a key electromagnetic (EM) signature that will contribute to the understanding of neutron star (NS) mergers.
Researchers have created a 98-milligram sensor system — about one tenth the weight of a jellybean or less than one-hundredth of an ounce — that can ride aboard a small drone or an insect, such as a moth, until it gets to its destination. Then, when a researcher sends a Bluetooth command, the sensor is released from its perch and can fall up to 72 feet — from about the sixth floor of a building — and land without breaking. Once on the ground, the sensor can collect data, such as temperature or humidity, for almost three years.
Physicists at the Naval Research Laboratory are collaborating with several universities throughout the U.S. to develop a small satellite that will detect the emission of short gamma-ray bursts. U.S. Naval Research Laboratory, Washington D.C. The U.S. Naval Research Laboratory (NRL), in partnership with NASA's Marshall Space Flight Center (MSFC), has developed StarBurst, a small satellite (SmallSat) instrument for NASA's StarBurst Multimessenger Pioneer mission, which will detect the emission of short gamma-ray bursts (GRBs), a key electromagnetic (EM) signature that will contribute to the understanding of neutron star (NS) mergers. NRL transferred the instrument to NASA on March 4 for the next phase, environmental testing. From there, the instrument will be integrated onto the spacecraft bus, followed by launch into Low Earth Orbit in 2027. StarBurst will be installed as a secondary payload via the Evolved Expendable Launch Vehicle Secondary Payload Adapter Grande interface with a
The Department of Defense (DoD) is developing technology for satellites to communicate via lasers. Laser communications could transmit data faster and more securely than traditional radio frequency communications. DoD has made progress in developing this technology, but it has also faced delays and other issues-and hasn't fully demonstrated that it works in space. Despite these challenges, DoD plans to continue to develop and launch hundreds of satellites worth billions of dollars that require the use of laser communications.
NearSpace Launch Inc. (NSL), a privately held and fully U.S.-owned aerospace company, is actively redefining the boundaries of responsive spaceflight through its development and deployment of the Train Rapid on Orbit Payload (TROOP) and ThinSat platforms. Over the past decade, NSL has launched more than 100 small satellites and over 900 flight systems and subsystems into orbit. NSL's satellites have been part of launches operated by Astra, Atlas, Delta, Firefly Aerospace, Northrop Grumman, Virgin Galactic and SpaceX among others. Headquartered in Upland, Indiana, NSL is currently the largest small satellite manufacturer in the midwestern region of the U.S., uniquely positioned to address urgent national needs for rapid space access and technology testing.
Airbus Defense London, UK aeron.a.haworth@airbus.com
Our MP42 satellite, which launched into low Earth orbit (LEO) two and a half years ago aboard the SpaceX Transporter-4 mission, recently took an unexpected hit from a small piece of space debris or micrometeoroid. The impact created a 6 mm hole, roughly the size of a chickpea, in one of its solar panels.
Letter from the Guest Editors
Increasing digitalization of the aircraft cabin, driven by the need for improved operational efficiency and an enhanced passenger experience, has led to the development of data-driven services. In order to implement these services, information from different systems is often required, which leads to a multi-system architecture. When designing a network that interconnects these systems, it is important to consider the heterogeneous device and supplier landscape as well as variations in the network architecture resulting from airline customization or cabin upgrades. The novel ARINC 853 Cabin Secure Media-Independent Messaging (CSMIM) standard addresses this challenge by specifying a communication protocol that relies on a data model to encode provided and consumed information. This paper presents an approach to integrate CSMIM-specific communication concepts into a Model-Based Systems Engineering (MBSE) framework using the Systems Modeling Language (SysML). This enables a streamlined
As a result of advancements to the Industrial Internet of Things (IIoT), companies across the globe are realizing the potential of smart manufacturing and connected business models. In fact, IoT connections are projected to more than double over the coming years: from 18 billion dollars in 2024 to 39.6 billion by 2033.
This SAE Aerospace Standard (AS) contains requirements for a digital time division command/response multiplex data bus, for use in systems integration that is functionally similar to MIL-STD-1553B with Notice 2 but with a star topology and some deleted functionality. Even with the use of this document, differences may exist between multiplex data buses in different system applications due to particular application requirements and the options allowed in this document. The system designer must recognize this fact and design the multiplex bus controller (BC) hardware and software to accommodate such differences. These designer selected options must exist to allow the necessary flexibility in the design of specific multiplex systems in order to provide for the control mechanism, architectural redundancy, degradation concept, and traffic patterns peculiar to the specific application requirements.
This Handbook is intended to accompany or incorporate AS5643, AS5643/1, AS5657, AS5706, and ARD5708. In addition, full understanding of this Handbook also requires knowledge of IEEE-1394-1995, IEEE-1394a, and IEEE-1394b standards. This Handbook contains detailed explanations and architecture analysis on AS5643, bus timing and scheduling considerations, system redundancy design considerations, suggestions on AS5643-based system configurations, cable selection guidance, and lessons learned on failure modes.
IEEE-1394b, Interface Requirements for Military and Aerospace Vehicle Applications, establishes the requirements for the use of IEEE Std 1394™-2008 as a data bus network in military and aerospace vehicles. The portion of IEEE Std 1394™-2008 standard used by AS5643 is referred to as IEEE-1394 Beta (formerly referred to as IEEE-1394b.) It defines the concept of operations and information flow on the network. As discussed in 1.4, this specification contains extensions/restrictions to “off-the-shelf” IEEE-1394 standards and assumes the reader already has a working knowledge of IEEE-1394. This document is referred to as the “base” specification, containing the generic requirements that specify data bus characteristics, data formats, and node operation. It is important to note that this specification is not designed to be stand-alone; several requirements leave the details to the implementations and delegate the actual implementation to be specified by the network architect/integrator for a
Recent advances are reducing the cost of space launch, high specific power solar cells, and the production of satellite systems. Modular architectures with no moving parts and distributed power systems would minimize assembly and maintenance costs. Together, this may enable space-based solar power to provide decarbonized dispatchable power at a lower cost than equivalent technologies such as nuclear power stations. Space-based Solar Power for Instantaneously Dispatchable Renewable Power on Earth discusses the advances in emerging technologies, like thin film solar cells, reusable launch vehicles, and mass-produced modular satellite systems that would make economic space power feasible. Click here to access the full SAE EDGETM Research Report portfolio.
This document defines a set of standard application layer interfaces called JAUS Manipulator Services. JAUS Services provide the means for software entities in an unmanned system or system of unmanned systems to communicate and coordinate their activities. The Manipulator Services represent platform-independent capabilities commonly found across domains and types of unmanned systems. At present, twenty-five (25) services are defined in this document. These services are categorized as: Low Level Manipulator Control Services – The one service in this category allows for low-level command of the manipulator joint actuation efforts. This is an open-loop command that could be used in a simple tele-operation scenario. The service in this category is listed as follows: Primitive Manipulator Service Manipulator Sensor Services – These services, when queried, return instantaneous sensor data. Three services are defined that return respectively joint positions, joint velocities, and joint
The SAE Aerospace Information Report AIR5315 – Generic Open Architecture (GOA) defines “a framework to identify interface classes for applying open systems to the design of a specific hardware/software system.” [sae] JAUS Service (Interface) Definition Language defines an XML schema for the interface definition of services at the Class 4L, or Application Layer, and Class 3L, or System Services Layer, of the Generic Open Architecture stack (see Figure 1). The specification of JAUS services shall be defined according to the JAUS Service (Interface) Definition Language document.
This document describes machine-to-machine (M2M)1 communication to enable cooperation between two or more traffic participants or CDA devices hosted or controlled by said traffic participants. The cooperation supports or enables performance of the dynamic driving task (DDT) for a subject vehicle equipped with an engaged driving automation system feature and a CDA device. Other participants may include other vehicles with driving automation feature(s) engaged, shared road users (e.g., drivers of conventional vehicles or pedestrians or cyclists carrying compatible personal devices), or compatible road operator devices (e.g., those used by personnel who maintain or operate traffic signals or work zones). Cooperative driving automation (CDA) aims to improve the safety and flow of traffic and/or facilitate road operations by supporting the safer and more efficient movement of multiple vehicles in proximity to one another. This is accomplished, for example, by sharing information that can be
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