Multipath-Assisted Radio Sensing and State Detection for the Connected Aircraft Cabin

Research output: Contribution to journalResearch articleContributedpeer-review



Efficiency and reliable turnaround time are core features of modern aircraft transportation and key to its future sustainability. Given the connected aircraft cabin, the deployment of digitized and interconnected sensors, devices and passengers provides comprehensive state detection within the cabin. More specifically, passenger localization and occupancy detection can be monitored using location-aware communication systems, also known as wireless sensor networks. These multi-purpose communication systems serve a variety of capabilities, ranging from passenger convenience communication services, over crew member devices, to maintenance planning. In addition, radio-based sensing enables an efficient sensory basis for state monitoring; e.g., passive seat occupancy detection. Within the scope of the connected aircraft cabin, this article presents a multipath-assisted radio sensing (MARS) approach using the propagation information of transmitted signals, which are provided by the channel impulse response (CIR) of the wireless communication channel. By performing a geometrical mapping of the CIR, reflection sources are revealed, and the occupancy state can be derived. For this task, both probabilistic filtering and k-nearest neighbor classification are discussed. In order to evaluate the proposed methods, passenger occupancy detection and state detection for the future automation of passenger safety announcements and checks are addressed. Therefore, experimental measurements are performed using commercially available wideband communication devices, both in close to ideal conditions in an RF anechoic chamber and a cabin seat mockup. In both environments, a reliable radio sensing state detection was achieved. In conclusion, this paper provides a basis for the future integration of energy and spectrally efficient joint communication and sensing radio systems within the connected aircraft cabin.


Original languageEnglish
Article number2859
Number of pages19
Issue number8
Publication statusPublished - Apr 2022

External IDs

Scopus 85127658003
PubMed 35458843
dblp journals/sensors/NinnemannSSM22
WOS 000785409200001
Mendeley 1fe2072b-66c4-3151-9f8f-a2e5872a65d2
unpaywall 10.3390/s22082859



  • aircraft boarding, beyond 5G (B5G), channel impulse response (CIR), connected aircraft cabin, k-nearest neighbor (kNN) classification, multipath-assisted radio sensing (MARS), occupancy detection, probabilistic grid mapping, ultra-wideband (UWB), wireless sensor network (WSN)