ADS-B based collision avoidance radar for unmanned aerial vehicles

Lai, Chieh-Ping; Ren, Yu‐Jiun; Lin, Chujen

doi:10.1109/mwsym.2009.5165638

Cited by 17 publications

(13 citation statements)

References 1 publication

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“…In contrast to radar-based ATC, the GPS and radio-based ADS-B system introduces a datalink over which traffic information and, potentially, instructions for UAVs could be transmitted. 11 It also makes all traffic visible to all aircraft (aircraft see exactly what ATC sees) instead of being limited to Traffic Alert and Avoidance System (TCAS) equipped aircraft. This will improve situational awareness for both manned aircraft and UAVs, lowering the risk of conflicts.…”

Section: A Airspace and Trafficmentioning

confidence: 99%

Flight Testing a UAV in Simulated Controlled Airspace

Dixit

Falusi

Kim

et al. 2013

AIAA Guidance, Navigation, and Control (GNC) Conference

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Novel airspace systems that integrate the latest technology advancements must be tested before widespread adoption. Despite the growing sophistication of simulation software, new systems must be practically tested before implementation. To facilitate the rapid prototyping of such architectures we present the flight test results of a low cost, small scale, modular airspace design. We incorporate flight data processing and control logic into an onboard iPhone 4 in small UAV aircraft. The iPhone 4 performs guidance, navigation, and control, while receiving desired trajectory information from a ground based laptop. We integrate these aircraft into a simulated air traffic environment and demonstrate automated two-way communications between aircraft and ground control tower. We present results of successful straight and level flight and trajectory tracking for a single aircraft.

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Section: A Airspace and Trafficmentioning

confidence: 99%

Flight Testing a UAV in Simulated Controlled Airspace

Dixit

Falusi

Kim

et al. 2013

AIAA Guidance, Navigation, and Control (GNC) Conference

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“…Existing works on studying the ADS‐B technology on UAVs focused more on a single device or a small‐scale fleet, such as references . NASA has been testing the ADS‐B technology in its latest UTM system for small‐scale UAV network management .…”

Section: Introductionmentioning

confidence: 99%

When UAVs coexist with manned airplanes: Large‐scale aerial network management using ADS‐B

Pan

et al. 2019

Trans Emerging Tel Tech

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Increasing attention has been paid to employing the Automatic Dependent Surveillance‐Broadcast (ADS‐B) technology on unmanned area vehicles (UAVs). The critical challenge therefore emerges, ie, how to effectively schedule the UAVs without interfering the communication. An UAV management framework named uFly is proposed to address this challenge by controlling the total ADS‐B communication traffic over the air. The ADS‐B's interference probability is first modeled. Based on this model, the UAVs' ADS‐B traffic (as well as the number of flying UAVs) should match the manned airplanes' signals. By taking the manned airplanes' signals as the first‐class constraint, uFly then dynamically approves or denies UAVs for flight based on the real‐time number of airplanes. Finally, experiments using different data sets are conducted to verify the superior performance of uFly.

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“…There are also several auxiliary systems that could provide the aircraft (or UAVs) with precise information about the state of the nearby traffic, such as the Automatic Dependent Surveillance Broadcast (ADS-B) system [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Cooperative Multi-UAV Collision Avoidance Based on Distributed Dynamic Optimization and Causal Analysis

Lao

Tang

2017

Applied Sciences

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Abstract:A critical requirement for unmanned aerial vehicles (UAV) is the collision avoidance (CA) capability to meet safety and flexibility issues in an environment of increasing air traffic densities. This paper proposes two efficient algorithms: conflict detection (CD) algorithm and conflict resolution (CR) algorithm. These two algorithms are the key components of the cooperative multi-UAV CA system. The CD sub-module analyzes the spatial-temporal information of four dimensional (4D) trajectory to detect potential collisions. The CR sub-module calculates the minimum deviation of the planned trajectory by an objective function integrated with track adjustment, distance, and time costs, taking into account the vehicle performance, state and separation constraints. Additionally, we extend the CR sub-module with causal analysis to generate all possible solution states in order to select the optimal strategy for a multi-threat scenario, considering the potential interactions among neighboring UAVs with a global scope of a cluster. Quantitative simulation experiments are conducted to validate the feasibility and scalability of the proposed CA system, as well as to test its efficiency with variable parameters.

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ADS-B based collision avoidance radar for unmanned aerial vehicles

Cited by 17 publications

References 1 publication

Flight Testing a UAV in Simulated Controlled Airspace

Flight Testing a UAV in Simulated Controlled Airspace

When UAVs coexist with manned airplanes: Large‐scale aerial network management using ADS‐B

Cooperative Multi-UAV Collision Avoidance Based on Distributed Dynamic Optimization and Causal Analysis

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