A Study on Deep Reinforcement Learning Framework for DME Pulse Design
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초록
The Distance Measuring Equipment (DME) is a ground-based aircraft navigation system and is considered as an infrastructure that ensures resilient aircraft navigation capability during the event of a Global Navigation Satellite System (GNSS) outage. The main problem of DME as a GNSS back up is a poor positioning accuracy that often reaches over 100 m. In this paper, a novel approach of applying deep reinforcement learning to a DME pulse design is introduced to improve the DME distance measuring accuracy. This method is designed to develop multipath-resistant DME pulses that comply with current DME specifications. In the research, a Markov Decision Process (MDP) for DME pulse design is set using pulse shape requirements and a timing error. Based on the designed MDP, we created an Environment called PulseEnv, which allows the agent representing a DME pulse shape to explore continuous space using the Soft Actor Critical (SAC) reinforcement learning algorithm.
Abstract
The Distance Measuring Equipment (DME) is a ground-based aircraft navigation system and is considered as an infrastructure that ensures resilient aircraft navigation capability during the event of a Global Navigation Satellite System (GNSS) outage. The main problem of DME as a GNSS back up is a poor positioning accuracy that often reaches over 100 m. In this paper, a novel approach of applying deep reinforcement learning to a DME pulse design is introduced to improve the DME distance measuring accuracy. This method is designed to develop multipath-resistant DME pulses that comply with current DME specifications. In the research, a Markov Decision Process (MDP) for DME pulse design is set using pulse shape requirements and a timing error. Based on the designed MDP, we created an Environment called PulseEnv, which allows the agent representing a DME pulse shape to explore continuous space using the Soft Actor Critical (SAC) reinforcement learning algorithm.
참고문헌 (8)
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- "Soft Actor-Critic Algorithms and Applications" (2019)[URL]
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- Euiho Kim, "Improving DME Performance for APNT Using Alternative Pulse and Multipath Mitigation", IEEE Transactions on Aerospace and Electronic Systems, 53(2), pp.877~887 (2017), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- Euiho Kim, "SFOL Pulse: A High Accuracy DME Pulse for Alternative Aircraft Position and Navigation", Sensors, 17(10), pp.2183~ (2017), MDPI AG[DOI]
- DME, "DME for Alternative Position, Navigation, and Timing (APNT), APNT White Paper", Lilley, R. W, 2012