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This article presents the first demonstration of navigation with cellular signals of opportunity (SOPs) on a high-altitude aircraft. An extensive flight campaign was conducted by the Autonomous Systems Perception, Intelligence, and Navigation Laboratory in collaboration with the U.S. Air Force to sample ambient downlink cellular SOPs in different regions in Southern California, USA. Carrier phase measurements were produced from these signals, which were subsequently fused in an extended Kalman filter along with altimeter measurements to estimate the aircraft’s state (position, velocity, and time). Three flights are performed in three different regions: 1) rural, 2) semiurban, and 3) urban. A multitude of flight trajectories and altitudes above ground level (AGL) was exercised in the three flights: 1) a 51-km trajectory of grid maneuvers with banking and straight segments at about 5,000 ft AGL, 2) a 57-km trajectory of a teardrop descent from 7,000 ft AGL down to touchdown at the runway, and 3) a 55-km trajectory of a holding pattern at about 15,000 ft AGL. The estimated aircraft trajectory is computed for each flight and compared with the trajectory from the aircraft’s onboard navigation system, which utilized a GPS receiver coupled with an inertial navigation system and an altimeter. The cellular SOPs produced remarkable sustained navigation accuracy over the entire flight trajectories in all three flights, achieving a 3D position root mean-squared error of 10.53 m, 4.96 m, and 15.44 m, respectively. [ABSTRACT FROM AUTHOR]

The aviation system has experienced an increasing demand over the last decade since it is considered one of the optimal means of transportation. As a result of this increasing demand, aviation organizations have been forced to focus on passenger safety by keeping aircraft airworthy at all times and by investing in the maintenance sector. Recent literature shows that the maintenance sector is still using outdated technology to maintain documentation of an aircraft's maintenance system. This article proposes the use of model-based system engineering (MBSE) as an approach to document aircraft maintenance systems. Systems modeling language (SysML) provides the maintenance system with a more systematic application that would automatically update maintenance records and provide stakeholders with more precise documentation. SysML is expressed through the use of structural and behavioral diagrams for the EA-6B aircraft. This article also provides a look into the use of SysML in the modeling of complex system architecture and the interaction between various systems. The integration of reliability studies and SysML is showcased through a case study. A failure mode and effect analysis is performed to show the usability of SysML in conducting reliability analysis. This article serves as a foundation for practitioners who aim to use MBSE methodology to solve the current setbacks existing in the maintenance aviation sector. [ABSTRACT FROM AUTHOR]

The KC-135R Stratotanker is a multifunction slim body aircraft that provides air refueling and airlift for the United States’ war and peacetime requirements, which demand a certain level of availability. As the KC-135R fleet ages, the aircraft availability (AA) rate degrades due to high demand use, stress, and the age of the equipment. Preventative and corrective maintenance is designed to return the aircraft to an available state to meet mission requirements, but the United States Air Force continues to fail at meeting every requirement communicated by commanders for KC-135R air refueling and airlift. Focusing on aircraft metrics can enable a prediction model of AA and provide the unit commanders the tools for data influenced decisions. The analysis of historical aircraft maintenance and flight metrics will show a correlation between tracked metrics and AA, thus, the ability to predict a future availability rate. Furthermore, analyzing the data with machine learning techniques will improve prediction accuracy by evaluating the variable importance and will make inferences learned from mining the data that are otherwise difficult to model in a complex system of systems. [ABSTRACT FROM AUTHOR]

Opportunistic navigation with cellular signals is studied and demonstrated on a high-altitude aircraft. An extensive campaign was conducted by the Autonomous Systems Perception, Intelligence, and Navigation Laboratory (ASPIN) in collaboration with the U.S. Air Force (USAF) to sample ambient cellular signals of opportunity (SOPs) at different altitudes in different regions in Southern California, USA. The carrier-to-noise ratio is characterized as a function of altitude and horizontal distance. It was found that signals from cellular transmitters can be reliably acquired and tracked for navigation purposes by receivers mounted on high dynamics aircraft flying at altitudes as high as 23,000 ft above ground level and horizontal distances as far as 100 km. The multipath channel is also characterized as a function of altitude, showing clean channels with a dominant line-of-sight component for altitudes up to 23,000 ft. To further assess the potential of cellular SOPs for aircraft navigation, a 51-km trajectory traversed over a period of 9 minutes was estimated exclusively using cellular SOPs (i.e., with no GPS or other sensors, except for barometric altimeter measurements), resulting in a three-dimensional position (3-D) 10.5-m position root-mean-squared error. [ABSTRACT FROM AUTHOR]

Automatic Carrier Landing System With Fixed Time Control [ABSTRACT FROM AUTHOR]

A controller that uses sum-of-squares programming is proposed for the attitude control of fixed-wing aircraft. Firstly, the vehicle’s state space form of attitude model is obtained by utilizing general mechanics. Then an online compute controller is designed to achieve the desired attitude tracking performance by solving contraction control metric related to the linearization area near the equilibrium point. Finally, the effectiveness of the control algorithm is demonstrated by a comparative simulation experiment. [ABSTRACT FROM AUTHOR]

Aircraft detection in synthetic aperture radar (SAR) imagery is a challenging task in SAR automatic target recognition (SAR ATR) areas due to aircraft’s extremely discrete appearance, obvious intraclass variation, small size, and serious background’s interference. In this article, a single shot detector (SSD), namely, attentional feature refinement and alignment network (AFRAN), is proposed for detecting aircraft in SAR images with competitive accuracy and speed. Specifically, three significant components, including attention feature fusion module (AFFM), deformable lateral connection module (DLCM), and anchor-guided detection module (ADM), are carefully designed in our method for refining and aligning informative characteristics of aircraft. To represent the characteristics of aircraft with less interference, low-level textural and high-level semantic features of aircraft are fused and refined in AFFM thoroughly. The alignment between aircraft’s discrete backscatting points and convolutional sampling spots is promoted in DLCM. Eventually, the locations of aircraft are predicted precisely in ADM based on aligned features revised by refined anchors. To evaluate the performance of our method, a self-built SAR aircraft sliced dataset and a large scene SAR image are collected. Extensive quantitative and qualitative experiments with detailed analysis illustrate the effectiveness of the three proposed components. Furthermore, the topmost detection accuracy and competitive speed are achieved by our method compared with other domain-specific methods, e.g., dense attention pyramid network (DAPN) and pyramid attention dilated network (PADN), and general convolutional neural network (CNN)-based methods, e.g., Feature Pyramid Network (FPN), Cascade R-CNN, SSD, RefineDet, and RepPoints Detector (RPDet). [ABSTRACT FROM AUTHOR]

Before Unmanned Aircraft Systems (UAS) can be widely deployed over complex terrain and urban regions, a methodology is needed to deconflict and track UAS flights. This paper presents a formal geofence definition and a methodology to use geofences to temporally and spatially organize the airspace in support of a UAS Traffic Management (UTM) system. Algorithms are presented to temporally and spatially deconflict requested geofences from existing approved geofences in the UTM system. A case study shows how deconflicted geofences impact UAS flight. [ABSTRACT FROM AUTHOR]

Autopilot failures have caused fatal results for both military and civilian applications, leading to loss of life and property. Major contributing factors are disturbances (e.g., winds), uncertainties (e.g., unmodeled dynamics and parameter variations), and couplings (e.g., a bank maneuver affecting pitch attitude). In this brief, a novel disturbance/uncertainty/coupling estimator structure is introduced for identifying and canceling these effects as a whole. A controller scheme based on the $\mathcal {H}_\infty$ design is implemented with explicit bounds for robust stability and robust performance. Validity of the proposed approach is illustrated under high winds, strong couplings, and large parameter variations. [ABSTRACT FROM AUTHOR]

Current US regulation is not equipped to provide explicit privacy protection for drone use in an era of sophisticated audio/video and social media. In 2016, the National Telecommunications and Information Association recognized this deficit by releasing a set of best practices, which we examine in light of the current privacy concerns with drone use in the US. [ABSTRACT FROM AUTHOR]

In air combat, an active countermeasure against an attacking missile homing into a Target aircraft entails the launch of a defending missile. The Target is protected by the Defender, which aims to intercept the Attacker before the latter reaches the Target aircraft. A differential game is presented where the Target–Defender team strives to maximize the terminal separation between the Target and the Attacker at the time instant where the Attacker is intercepted by the Defender, whereas the Attacker strives to minimize the said separation. This paper discusses the case where the Defender is endowed with a positive capture radius. Optimal strategies for the three agents are derived and simulation examples illustrate the effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]

Recently, unmanned aircraft systems (UASs) have attracted attention as a new avenue for commercial services. Using the flexible mobility of unmanned aircrafts (UAs), commercial services can be operated in wide areas. However, there is a problem in the wireless communication between the UA and its ground station. When several UASs are operated within the neighboring airspace, wireless-communication conflicts occur. One of the most effective solutions for this issue is to decide the communication schedule using a time-division multiple access (TDMA) scheme. Furthermore, by spatially reusing the time slot, numerous UAs can be operated within the neighboring airspace, in a limited frequency band. In this paper, we propose an efficient time-slot allocation for enhancing the frequency resource utilization. Our proposed scheme determines the time-slot allocation considering the time-slot spatial reuse, using a virtual cell based space partitioning method. In addition, we consider the influence of the UA mobility on the network to decide the parameters for the proposed resource allocation system. The effectiveness of our proposed resource allocation is evaluated through computer-based simulation. [ABSTRACT FROM PUBLISHER]

Collision avoidance strategies for multiple unmanned aerial vehicles (UAVs) based on geometry are investigated in this study. The proposed strategies allow a group of UAVs to avoid obstacles and separate if necessary through a simple algorithm with low computation by expanding the collision-cone approach to formation of UAVs. The geometric approach uses line-of-sight vectors and relative velocity vectors where dynamic constraints are included in the formation. Each UAV can determine which plane and direction are available for collision avoidance. An analysis is performed to define an envelope for collision avoidance, where angular rate limits and obstacle detection range limits are considered. Based on the collision avoidance envelope, each UAV in a formation determines whether the formation can be maintained or not while avoiding obstacles. Numerical simulations are performed to demonstrate the performance of the proposed strategies. [ABSTRACT FROM AUTHOR]