Airborne Radar-Based Collision Detection and Risk Estimation for Small Unmanned Aircraft Systems

Sahawneh, Laith R.; Mackie, James; Spencer, Jonathan; Beard, Randal W.; Warnick, Karl F.

doi:10.2514/1.i010284

Cited by 13 publications

(5 citation statements)

References 37 publications

(54 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When the acquired target information meets the common track criteria, the target will be detected by the radar system. [23][24][25] We focused on analyzing the radar detection probability of a stealth UAV in a network radar environment.…”

Section: Network Radar Detection Systemmentioning

confidence: 99%

Optimal path planning with modified A-Star algorithm for stealth unmanned aerial vehicles in 3D network radar environment

Zhang

Dai

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

For stealth unmanned aerial vehicles (UAVs), path security and search efficiency of penetration paths are the two most important factors in performing missions. This article investigates an optimal penetration path planning method that simultaneously considers the principles of kinematics, the dynamic radar cross-section of stealth UAVs, and the network radar system. By introducing the radar threat estimation function and a 3D bidirectional sector multilayer variable step search strategy into the conventional A-Star algorithm, a modified A-Star algorithm was proposed which aims to satisfy waypoint accuracy and the algorithm searching efficiency. Next, using the proposed penetration path planning method, new waypoints were selected simultaneously which satisfy the attitude angle constraints and rank-K fusion criterion of the radar system. Furthermore, for comparative analysis of different algorithms, the conventional A-Star algorithm, bidirectional multilayer A-Star algorithm, and modified A-Star algorithm were utilized to settle the penetration path problem that UAVs experience under various threat scenarios. Finally, the simulation results indicate that the paths obtained by employing the modified algorithm have optimal path costs and higher safety in a 3D complex network radar environment, which show the effectiveness of the proposed path planning scheme.

show abstract

Section: Network Radar Detection Systemmentioning

confidence: 99%

Optimal path planning with modified A-Star algorithm for stealth unmanned aerial vehicles in 3D network radar environment

Zhang

Dai

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

show abstract

“…Also, many researchers used MATLAB tools [60][61][62][63][64] to simulate their UAVs and scenarios, with most of the work being very limited to certain types or aspects of UAVs. However, many of these simulators such as X-Plane, FlightGear, and FSX take the aircraft input commands through regular computer input devices such as keyboards, joysticks, or Software APIs.…”

Section: Literature Reviewmentioning

confidence: 99%

UTSim: A framework and simulator for UAV air traffic integration, control, and communication

Al-Mousa

Sababha

Al-Madi

et al. 2019

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

The interest in unmanned systems especially unmanned aerial vehicle is continuously increasing. Unmanned aerial vehicles started to become of great benefit in many different fields. It is anticipated that unmanned aerial vehicles will soon become a main component of the future urban air traffic. The integration of unmanned aerial vehicles within existing air traffic environments has started getting the attention of researchers. Integrating unmanned systems in the real-world urban air traffic requires the development of tools and simulators to enable researchers in their ongoing efforts. In this article, a simulator called UTSim is introduced. The proposed simulator is built using the Unity platform. UTSim is capable of simulating unmanned aerial vehicle physical specification, navigation, control, communication, sensing and avoidance in environments with static and moving objects. The simulator enables studying and exploring several unmanned aerial vehicle air traffic integration issues like sense and avoid, communication protocols, navigation algorithms, and much more. UTSim is designed and developed to be easily used. The user can specify the properties of the environment, the number and types of unmanned aerial vehicles in the environment, and specify the algorithm to be used for path planning and collision avoidance. The simulator outputs a log file with a lot of useful information such as the number of sent and received messages, the number of detected objects and collided unmanned aerial vehicles. Three scenarios have been implemented in this article to present the capabilities of UTSim and to illustrate how it can benefit researchers in the field of integrating unmanned aerial vehicles in urban air traffic.

show abstract

“…The performance of the proposed conflict/collision detection approach is quantified using the probability of correct detection P cd and the probability of false alarm P fa (Sahawneh, Mackie, Spencer, Beard, & Warnick, 2015;Kuchar, 1996). If N is the number of performed simulations, among which there are E true conflict/collision events, and the proposed conflict/collision detection algorithm detects M conflicts/collisions, among which e E detections are the correct conflict/collision detections, then the correct detection rate P cd and false alarm rate P fa are given by…”

Section: Number Of Intrudersmentioning

confidence: 99%

Detect and Avoid for Small Unmanned Aircraft Systems Using ADS-B

Sahawneh

Duffield

Beard

et al. 2015

Air Traffic Control Quarterly

Self Cite

View full text Add to dashboard Cite

With the increasing demand to integrate unmanned aircraft systems (UAS) into the National Airspace System (NAS), new procedures and technologies are necessary to ensure safe airspace operations and minimize the impact of UAS on current airspace users. Currently, small UAS face limitations on their utilization in civil airspace because they do not have the ability to detect and avoid other aircraft. In this article, we will present a framework that consists of an Automatic Dependent Surveillance-Broadcast (ADS-B)-based sensor, track estimator, conflict/collision detection, and resolution that mitigates collision risk. ADS-B o↵ers long range, omni-directional intruder detection with comparatively few size, weight, power, and cost demands. The proposed conflict/collision detection and planning algorithms for conflict/collision resolution are designed in the local level frame, which is unrolled, unpitched body frame where the ownship is stationary at the center of the map. The path planning method is designed to be multi-resolutional at increasing distance from the ownship to account for both self-separation and collision avoidance thresholds. We demonstrate and validate this approach using simulated ADS-B measurements.

show abstract

Airborne Radar-Based Collision Detection and Risk Estimation for Small Unmanned Aircraft Systems

Cited by 13 publications

References 37 publications

Optimal path planning with modified A-Star algorithm for stealth unmanned aerial vehicles in 3D network radar environment

Optimal path planning with modified A-Star algorithm for stealth unmanned aerial vehicles in 3D network radar environment

UTSim: A framework and simulator for UAV air traffic integration, control, and communication

Detect and Avoid for Small Unmanned Aircraft Systems Using ADS-B

Contact Info

Product

Resources

About