Airborne Systems Research Articles

Formal Analysis and Verification of Airborne Software Based on DO-333

With rapid technological advances in airborne control systems, it has become imperative to ensure the reliability, robustness, and adaptability of airborne software since failure of these software could result in catastrophic loss of property and life. DO-333 is a supplement to the DO-178C standard, which is dedicated to guiding the application of formal methods in the review and analysis of airborne software development processes. However, DO-333 lacks theoretical guidance on how to choose appropriate formal methods and tools to achieve verification objectives at each stage of the verification process, thereby limiting their practical application. This paper is intended to illustrate the formal methods and tools available in the verification process to lay down a general guide for the formal development and verification of airborne software. We utilized the Air Data Computer (ADC) software as the research object and applied different formal methods to verify software lifecycle artifacts. This example explains how to apply formal methods in practical applications and proves the effectiveness of formal methods in the verification of airborne software.

High Definition 3D Map Creation Using GNSS/IMU/LiDAR Sensor Integration to Support Autonomous Vehicle Navigation.

Recent developments in sensor technologies such as Global Navigation Satellite Systems (GNSS), Inertial Measurement Unit (IMU), Light Detection and Ranging (LiDAR), radar, and camera have led to emerging state-of-the-art autonomous systems, such as driverless vehicles or UAS (Unmanned Airborne Systems) swarms. These technologies necessitate the use of accurate object space information about the physical environment around the platform. This information can be generally provided by the suitable selection of the sensors, including sensor types and capabilities, the number of sensors, and their spatial arrangement. Since all these sensor technologies have different error sources and characteristics, rigorous sensor modeling is needed to eliminate/mitigate errors to obtain an accurate, reliable, and robust integrated solution. Mobile mapping systems are very similar to autonomous vehicles in terms of being able to reconstruct the environment around the platforms. However, they differ a lot in operations and objectives. Mobile mapping vehicles use professional grade sensors, such as geodetic grade GNSS, tactical grade IMU, mobile LiDAR, and metric cameras, and the solution is created in post-processing. In contrast, autonomous vehicles use simple/inexpensive sensors, require real-time operations, and are primarily interested in identifying and tracking moving objects. In this study, the main objective was to assess the performance potential of autonomous vehicle sensor systems to obtain high-definition maps based on only using Velodyne sensor data for creating accurate point clouds. In other words, no other sensor data were considered in this investigation. The results have confirmed that cm-level accuracy can be achieved.

Improved Passive SAR Imaging With DVB-T Transmissions

This article investigates passive synthetic aperture radar (SAR) image formation using Terrestrial Digital Video Broadcast (DVB-T) transmitters of opportunity and an airborne receiver. The proposed airborne system does not use separate channels for direct and reflected signal reception. The proposed image formation algorithm suppresses artifacts due to the presence of the direct signal in radar echo data using modified CLEAN method and accounts for unknown irregularities in airborne platform motion using a map-drift autofocus (MDA) technique. The algorithms are theoretically derived and experimentally confirmed via an appropriate airborne campaign, and their experimental performance is measured.

Fully Automated Profile-based Calibration Strategy for Airborne and Terrestrial Mobile LiDAR Systems with Spinning Multi-beam Laser Units

LiDAR-based mobile mapping systems (MMS) are rapidly gaining popularity for a multitude of applications due to their ability to provide complete and accurate 3D point clouds for any and every scene of interest. However, an accurate calibration technique for such systems is needed in order to unleash their full potential. In this paper, we propose a fully automated profile-based strategy for the calibration of LiDAR-based MMS. The proposed technique is validated by comparing its accuracy against the expected point positioning accuracy for the point cloud based on the used sensors’ specifications. The proposed strategy was seen to reduce the misalignment between different tracks from approximately 2 to 3 m before calibration down to less than 2 cm after calibration for airborne as well as terrestrial mobile LiDAR mapping systems. In other words, the proposed calibration strategy can converge to correct estimates of mounting parameters, even in cases where the initial estimates are significantly different from the true values. Furthermore, the results from the proposed strategy are also verified by comparing them to those from an existing manually-assisted feature-based calibration strategy. The major contribution of the proposed strategy is its ability to conduct the calibration of airborne and wheel-based mobile systems without any requirement for specially designed targets or features in the surrounding environment. The above claims are validated using experimental results conducted for three different MMS – two airborne and one terrestrial – with one or more LiDAR unit.

Leveraging Fog Computing for Sustainable Smart Farming Using Distributed Simulation

The concept of smart farming has led to the use of technology to enhance agricultural productivity. With access to low-cost sensors and management systems, more farmers are adopting this technology to achieve sustainable growth. However, in literature, there are no simulation platforms to help researchers and users understand sensor deployment, and data collection and processing. In this article, we propose a framework designed to provide a complete farming ecosystem. The toolkit facilitates users to simulate custom farming scenarios, specifically to identify sensor placement, coverage area, line-of-sight deployment, and data gathering through the relay mechanism or airborne systems, mobility models for mobile nodes, energy models for on-ground sensors and airborne vehicles, and backend computing support using the fog computing paradigm. Furthermore, in most of the existing works, network parameters are ignored, which can impact the overall performance of any deployed system. Therefore, the proposed framework also provides a benchmark in terms of transmission delay, packet delivery ratio, energy consumption, and system resources usage.

Automating Certification Objectives with SpeAR

The Speci cation and Analysis of Requirements (SpeAR) tool is a requirements prototyping and analysis tool based on the formal semantics of the Lustre language. It features a domain speci c language that formally captures functional requirements of systems or software. Once formalized, requirements can be analyzed to demonstrate correct- ness, consistency, and traceability using in nite-state model checking tools, such as JKind. The formal notation and analyses that SpeAR supports can be used to automate activities related to certi cation of safety critical software as suggested by DO-178C: Software Considera- tions in Airborne Systems and Equipment Certi cation. This standard de nes a rigorous software development process that ensures that soft- ware development activities produce object code that implement sys- tem requirements correctly, while introducing no additional functional- ity. Recent updates to the guidance allow for the use of formal methods to satisfy DO-178C certi cation objectives as outlined in DO-333: For- mal Methods Supplement to DO-178C and DO-278A. This paper walks through an e ort in which SpeAR is used to automate certi cation ac- tivities for production avionics software. It focuses on the use of SpeAR to address veri cation objectives related to the software design artifacts of DO-178C, replacing manual peer review activities with more rigorous formal-methods based analyses.

Mathematical modelling of an airborne technical vision system development

An airborne technical vision system of a modern aircraft is, on the one hand, a complex of multispectral sensors and, on the other, airborne computer equipment. The onboard computer solves a wide range of complex digital image processing tasks. The strict requirements are imposed on the computer mathematical software on the image processing time and on the quality of the result displayed on the pilot screen. The software development for such a complex system involves mathematical modelling and use modern information technologies in process of computational algorithms development for task solving. The proposed work discusses ways of solving subtasks of one of the most important subsystems of the airborne complex - the image fusion subsystem and solving the inverse navigation problem. The subsystem is represented by two blocks of tasks: tasks of primary image processing and high-level tasks. The primary processing unit solves the problems of image noise suppression, image enhancement, image fusion and edge detection. In the high-level block of tasks, the tasks of key points detection on real and virtual images, the tasks of a geometric transformation estimation of one image to the plane of another, and the task of a 3D model construction of the underlying surface are solved. The paper presents the results of mathematical modelling in the process of algorithms development for above problems solving. The new results of mathematical modelling of the noise estimation problem are presented in detail. The description of methods and results of other problems solving is less detailed due to article limit but provided with links to the corresponding publications of the authors.

A High-Precision Random Forest-Based Maximum Lyapunov Exponent Prediction Model for Spherical Porous Gas Bearing Systems

Spherical porous air bearing (SPAB) systems have been extensively used in various mechanical engineering applications. SPABs are promising materials in high-rotational speed, high-precision, and high-stiffness instruments. In SPAB systems, a rotor is supported by gas bearings, which provides higher rotational speed and lower heat generation environment than oil bearings do. Furthermore, SPAB does not cause deformation. Although, the supporting force of gas bearings is less, their stability is better than that of oil films. However, because the pressure distribution in the gas films is nonlinear, they are prone to failure at specific critical speeds, rotor imbalances, or inappropriate operations, which results in nonperiodic or chaotic motion and causes structural fatigue to the system. To understand and control the operating conditions of the SPAB systems during the nonperiodic motion, first, the governing equations of the SPAB system were solved to obtain the dynamic behavior of the rotor center. Then, the performance of the SPAB system were examined under different operating conditions by generating the maximum Lyapunov exponents (MLEs). However, the calculation process of MLE is extremely time consuming and complex. To solve this problem efficiently, a high-precision machine learning (ML)-based MLE prediction model was proposed in this study. The results show that the training process can be finished within few minutes, and the prediction process is able to be completed within few seconds. Meanwhile, the results demonstrate the merit of using the machine learning method for solving the MLE prediction problem and shorten the calculation time significantly. The proposed prediction model achieves excellent prediction outcome and it is more efficient and precise than traditional iteration scheme for the calculation of MLE. The feasibility of the proposed model is validated and the results also are the major contribution of this study.

A Framework for Evaluating the Standards for the Production of Airborne and Ground Traffic Management Software

The development of Airborne and Ground systems is framed by specific regulations, usually expressed as standards. A disadvantage of those standards is the inherent complexity for its application and the verification of compliance given the high number of requirements to be checked in many different situations of the application and which are highly dependent on the applicable level of criticality. When the development of this type of system requires the incorporation of new personnel without enough knowledge about the standards, risks of mistakes in their application grow exponentially. The objective of this work is to develop an Expert System (ES) that helps to evaluate the application of the standards DO-178C and DO-278A throughout the project life cycle, at the same time it serves to facilitate both its use and the learning of its application to a wide group of professionals. The proposed underlying method for the ES will allow evaluating the set of development processes to check coverage of the standards DO-178C and DO-278A without depending on a specific life cycle model. The method involves a model of the set of processes, so they can be evaluated by the ES. Additionally, the ES will require a minimum configuration to evaluate the development of systems based on these two standards. The main result is a new generic Expert System based on rules capable of being adapted to different environment of evaluation, whichh minor configuration operations thus allowing that a Generic ES can act as a Specific ES for each situation. This configurable ES has been customized to evaluate the software life cycle based on the standards under study.

Modular and Integrated Sensor Network of Intelligent Radiation Monitor Systems for Radiological and Nuclear Threat Response

Increased sensitivity to nuclear safety and security issues has prompted public entities and private institutions to maximize their capability to rapidly assess risks and intervene in the case of accident or threat. Quick intervention and response are achieved through nuclear measurements via airborne, land, and underwater systems. A network of cohesive, well-integrated and easy deployable radiation monitoring systems combined with real-time analysis of data is essential to facilitate and enhance the decision-making process during these most critical moments enhancing the quality of the management plan. The presented radiation monitoring systems can be integrated in several form factors which depend mainly on operational needs and internal battery for autonomous operation. Compact ARM based computers is embedded, which can store large amount of data in their non-volatile memory, run automatic data analysis and trigger alarms in case of exceeding radiation levels. All the systems can communicate with redundant interfaces in failover configuration and upload the acquired environmental information in a central database. The same monitoring systems can alert the emergency response personnel on the field as well, through wireless connection to common tablets or cellphone or SMS, guaranteeing a prompt response in case an illicit transportation of radiological or nuclear material is detected.

An Airborne Sonar System for Underwater Remote Sensing and Imaging

High-resolution imaging and mapping of the ocean and its floor has been limited to less than 5% of the global waters due to technological barriers. Whereas sonar is the primary contributor to existing underwater imagery, the water-based system is limited in spatial coverage due to its low imaging throughput. On the other hand, aerial synthetic aperture radar systems have provided high-resolution imaging of the entire earth's landscapes but are incapable of deep penetration into water. In this work, we present a proof-of-concept system which bridges the gap between electromagnetic imaging in air and sonar imaging in water through the laser-induced photoacoustic effect and high-sensitivity airborne ultrasonic detection. Here, we use air-coupled capacitive micromachined ultrasonic transducers (CMUTs) which is a critical differentiator from previous works and has enabled the acquisition of an underwater image from a fully airborne acoustic imaging system - a task that has yet to be accomplished in the literature. With the entire imaging system located on an airborne platform, there is much promise for the scalability of our system to one which could perform high-throughput imaging of underwater in large-scale deployment. Non-contact acoustic-based imaging modalities are also of much interest to the medical imaging and non-destructive testing communities. Incorporating air-coupled transducers, for example CMUTs, or other resonant sensors in these applications could be aided by the analysis presented throughout this work.

Can Mineral Oil Slicks Be Distinguished From Newly Formed Sea Ice Using Synthetic Aperture Radar?

In this feasibility study discriminating oil slicks and newly formed sea ice using synthetic aperture radar (SAR) imagery is investigated, using imagery from the L-band high-resolution uninhabited aerial vehicle synthetic aperture radar (UAVSAR) airborne and the satellite C-band RADARSAT-2 (RS-2) systems. To determine the separability of these two varying but similar appearing low backscatter ocean surfaces, multipolarization features are utilized from both SAR datasets. The discrimination is evaluated using the Kolmogorov–Smirnov separability test. All imagery was obtained during several sea ice campaigns in the Arctic Ocean and separate oil spill campaigns in Norway and the Gulf of Mexico, with each campaign collecting in situ observations. We observe that the polarization difference (VV-HH) reliably separates the mineral oil slicks and newly formed sea ice areas using UAVSAR images, due to the low noise floor and subsequent high signal-to-noise ratio (SNR) radiometric performance of the airborne system. The comparably higher noise floor and related lower SNR hampers the separability in the RS-2 images. Simulated noise floors were generated by adding white Gaussian noise to the UAVSAR data, which show that discrimination between the two low backscatter phenomena using multipolarization features is possible, provided that both datasets are still well above the noise floor. The pixel resolution has a limited effect on the separability. The results of this study provide an approach to distinguish oil slicks from newly formed sea ice, which might be of special interest should an oil spill occur within the marginal ice zone.

PaRTAA: A Real-time Multiprocessor for Mixed-Criticality Airborne Systems

Mixed-criticality systems, where multiple systems with varying criticality-levels share a single hardware platform, require isolation between tasks with different criticality-levels. Isolation can be achieved with software-based solutions or can be enforced by a hardware level partitioning. An asymmetric multiprocessor architecture offers hardware-based isolation at the cost of underutilized hardware resources, and the inter-core communication mechanism is often a single point of failure in such architectures. In contrast, a partitioned uniprocessor offers efficient resource utilization at the cost of limited scalability. We propose a partitioned real-time asymmetric architecture (PaRTAA) specifically designed for mixed-criticality airborne systems, featuring robust partitioning within processing elements for establishing isolation between tasks with varying criticality. The granularity in the processing element offers efficient resource utilization where inter-dependent tasks share the same processing element for sequential execution while preserving isolation, and independent tasks simultaneously execute on different processing elements as per system requirements.

CONCEPT OF INTEGRATED AIRBORNE SYSTEMS FOR PROVIDING AIRCRAFT OPERATIONS SAFETY, INCLUDING SYSTEMS FOR MONITORING THE FUNCTIONAL STATE OF THE OPERATOR

The development of modern civil and military aircraft is characterized by a rapid increase in the degree of functionality due to the requirements of today and the expansion of the scope of tasks to be solved. In military aviation, this feature is due to a significant expansion of the area of combat employment in terms of the enemy's active opposition, and in civil aviation, it can be explained by a large-scale implementation of technical means of flight control automation and landing under the conditions of high flights traffic in urban areas. In this regard, there was a fundamentally important transition from the separate design of airframes and components to the design of aircraft systems (AS) which represent a single complex system that solves many interdependent and interrelated tasks. Of course, such systems need technical diagnostics, real-time performance testing, and forecasting the remaining resource. This paper presents and describes the main scientific and technical ways to develop and create integrated airborne systems for providing flight safety of aircraft, including systems for monitoring the functional state of the pilot. The article considers the main methods and means for diagnostics and prognostics of the technical condition of an airframe and the critical units of aircraft. Their comparative analysis is carried out and a block diagram of an integrated diagnostic system is proposed. The essence of this system is to implement the procedure for accumulating flight data on the parameters of critical components and units on board aircraft and using a rapid-analysis method that involves monitoring the dynamics of changes in the trend of the controlled parameters in relation to limit values in real-time mode.

Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8

Thermal imagery is widely used in various fields of remote sensing. In this study, a novel processing scheme is developed to process the data acquired by the oblique airborne photogrammetric system AOS-Tx8 consisting of four thermal cameras and four RGB cameras with the goal of large-scale area thermal attribute mapping. In order to merge 3D RGB data and 3D thermal data, registration is conducted in four steps: First, thermal and RGB point clouds are generated independently by applying structure from motion (SfM) photogrammetry to both the thermal and RGB imagery. Next, a coarse point cloud registration is performed by the support of georeferencing data (global positioning system, GPS). Subsequently, a fine point cloud registration is conducted by octree-based iterative closest point (ICP). Finally, three different texture mapping strategies are compared. Experimental results showed that the global image pose refinement outperforms the other two strategies at registration accuracy between thermal imagery and RGB point cloud. Potential building thermal leakages in large areas can be fast detected in the generated texture mapping results. Furthermore, a combination of the proposed workflow and the oblique airborne system allows for a detailed thermal analysis of building roofs and facades.

MATHEMATICAL MODEL FOR SOLVING THE NAVIGATION PROBLEM AND ANGULAR ORIENTATION SPACECRAFT

Currently, there is an increased interest in the creation of strapdown inertial navigation systems (SINS), which make up the information core of modern airborne systems for the orientation and navigation of spacecraft (SC). An urgent problem arises, which is associated with the development of high-precision algorithms for estimating and filtering data from the sensors of the SC motion parameters, the mathematical model of the SINS, calculating its errors and analyzing the effect of errors on the characteristics of the navigation system and orientation of the SC. A mathematical model is proposed for solving the problem of navigation and angular orientation of a small SC equipped with electromagnetic control elements, taking into account the filtering of “noisy” magnetometer data. The requirements are set for the accuracy of the angular orientation and stabilization of the SC in the mode of maintaining the triaxial orientation of the SC in the orbital coordinate system (OCS) and for the duration of the damping mode of the angular velocities obtained by the SC during separation from the launch vehicle (LV), and the mode of the initial construction of the triaxial orientation of the SC in OCS. The mathematical model includes: a model of the motion of the center of mass of the SC in the osculating elements of the orbit with specified parameters, a model of the angular motion of the SC around the center of mass, a model of the Earth’s magnetic field (EMF) and a model of filtering magnetometer data. As an arithm for filtering data from a magnetometer on the components of the magnetic induction vector of the EMF, a one-parameter algorithm of exponential smoothing (exponential moving average) is used, which belongs to the class of first-order filters with an infinite impulse response. The results of numerical simulation of the dynamic processes of navigation and the angular orientation of the SC after separation from the LV taking into account the filtering of magnetometer data by the method of exponential smoothing using mathematical models are presented, and the accuracy of the angular orientation and stabilization of the SC is estimated.

Experimental study on flow-induced motions of TLP focusing on effects of appendages and mass ratio

Flow-induced motion (FIM) is an important issue for deep-draft floating platforms, reducing the fatigue life of mooring and riser systems. Tension leg platforms (TLPs) with a smaller mass ratio (mr, the ratio of the platform mass to the displacement), may experience more pronounced FIM responses in current. To investigate the FIM behavior of TLPs in towing tests, this research adopts an air-bearing system, mainly composed of low-friction air bearings and a smooth flat plate, to accurately simulate the mass ratio. The results demonstrated that in the range of 0.64≤mr≤0.90, the transverse amplitudes did not decrease with an increase in the mass ratio because the Scruton number Sc did not exceed 0.1. Through model tests, the effect of appendages on the FIM of TLPs was also examined. The results of the screening tests from 0∘ to 360∘ with an interval of 22.5∘ indicated that the transverse response is characterized by symmetry with a cycle of 90∘, while the yaw motion exhibits asymmetry owing to the effect of appendages. The largest transverse amplitude was obtained at 90 ∘, with a value of Ay∕D=0.408 occurring at Ur=7. In comparison with the bare hull platform, the transverse amplitude of the TLP with appendages significantly decreased by approximately 82% in the range of 6≤Ur≤8 at 45∘. Overall, these substantial results are expected to improve the understanding of the FIM characteristics of TLPs, and to provide benchmark data for design and numerical prediction as well.

Performance enhancement of nested hexagonal ring‐shaped compact multiband integrated wideband fractal antennas for wireless applications

In this paper, nested hexagonal ring-shaped fractal antennas are designed and investigated which are different from each other in patch orientation. Initially, the multiband integrated wideband hexagonal nested ring antenna is designed (antenna-I). To improve the multiband/wideband behavior, the patch orientation of antenna-I is changed to −60°/60° (antenna-II), −120°/120° (antenna-III), and −180°/180° (antenna-IV). Antennas are designed on low cost FR-4 glass epoxy substrate with relative permittivity of 4.4 and overall dimension 30 × 30 × 1.6 mm3. Comparison among antennas have been made and found that the antennas with negative orientation exhibit better results in terms of bandwidth, impedance matching, number of frequency bands, and gain. Designed antennas have been compared with each other and found that antennas-II and III are better in performance as compared to antennas-I and IV. Antenna-II exhibits wider bandwidth of 1.26 (2.52-3.78 GHz), 2.75 (4.03-6.78 GHz), and 6.1 GHz (7.82-13.92 GHz) with maximum gain of 7.14 dB. Similarly; antenna-III exhibits the bandwidth of 340 MHz (1.92-2.26 GHz), 820 MHz (3.04-3.86 GHz), 4230 MHz (5.38-9.61 GHz), and 3040 MHz (10.41-13.45 GHz) with a maximum gain of 6.19 dB. Prototype of the designed antennas with satisfactory orientations are fabricated and tested for the validation of results. Simulated and measured results are also juxtaposed and observed in good agreement with each other. Antennas exhibit bidirectional and omnidirectional pattern in E-plane and H-plane, respectively, also the radiation efficiency of antennas are in acceptable range from 75% to 95%. Due to the wider bandwidth of designed antennas, they can be used for different wireless standards such as Advance Wireless Services AWS-1, AWS-2, AWS-3, Wi-MAX, WLAN, X-band satellite communication, point-to-point wireless applications, ITU band, military satellite communication, television broadcasting, and military land and airborne systems.

Verification and testing of safety-critical airborne systems: A model-based methodology

In this paper, we address the issues of safety-critical software verification and testing that are key requirements for achieving DO-178C and DO- 331 regulatory compliance for airborne systems. Formal verification and testing are considered two different activities within airborne standards and they belong to two different levels in the avionics software development cycle. The objective is to integrate model-based verification and model-based testing within a single framework and to capture the benefits of their cross-fertilization. This is achieved by proposing a new methodology for the verification and testing of parallel communicating agents based on formal models. In this work, properties are extracted from requirements and formally verified at the design level, while the verified properties are propagated to the implementation level and checked via testing. The contributions of this paper are a methodology that integrates verification and testing, formal verification of some safety critical software properties, and a testing method for Modified Condition/Decision Coverage (MC/DC). The results of formal verification and testing can be used as evidence for avionics software certification.

Interference Environment Model Recognition for Robust Adaptive Detection

The recognition of the interference environment for adaptive radar detection is addressed in this article. Typically, detectors are designed in one specific scenario which may not be appropriate for the varying interference environment, especially for the airborne and space-based radar system. In this article, the considered recognition task is cast in terms of multiple hypothesis tests and the theory of model order selection (MOS) techniques are exploited to devise suitable decision rules. The interference environments are divided into homogeneity, partial homogeneity, and spherically invariant random process. Three MOS techniques, namely, the Akaike information criterion (AIC), generalized information criterion, and corrected AIC, are adopted. At the analysis stage, illustrating examples for the influence of the environment model parameters on the recognition accuracy of the MOS rules are presented. Numerical experiments show the AIC rule has the most robust recognition performance.