2022
DOI: 10.1109/tvt.2021.3129917
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Indoor Drone Positioning: Accuracy and Cost Trade-Off for Sensor Fusion

Abstract: Indoor drone or Unmanned Aerial Vehicle (UAV) operations, automated or with pilot control, are an upcoming and exciting subset of drone use cases. Automated indoor flights tighten the requirements of stability and localization accuracy in comparison with the classic outdoor use cases which rely primarily on (RTK) GNSS for localization. In this paper the effect of multiple sensors on 3D indoor position accuracy is investigated using the flexible sensor fusion platform OASE. This evaluation is based on real-life… Show more

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Cited by 33 publications
(20 citation statements)
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References 36 publications
(31 reference statements)
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“…The drone (i.e., the flying RFID reader) is tracked by a sensor fusion-based scheme that has fused the results from Decawave UWB and other low-cost directional sensors (IMU, magnetometer, etc.) based on an extended Kalman filter (EKF) [12,13]. For the RFID interrogation, a lightweight reader ThingMagic M6E-Micro [4]) is utilized.…”
Section: Experimental Evaluationmentioning
confidence: 99%
“…The drone (i.e., the flying RFID reader) is tracked by a sensor fusion-based scheme that has fused the results from Decawave UWB and other low-cost directional sensors (IMU, magnetometer, etc.) based on an extended Kalman filter (EKF) [12,13]. For the RFID interrogation, a lightweight reader ThingMagic M6E-Micro [4]) is utilized.…”
Section: Experimental Evaluationmentioning
confidence: 99%
“…They used acoustic, image/video, and wireless RF signals as system inputs. As UAV indoor flights place greater emphasis on stability and localization accuracy, Gerwen emphet al in [8] used a flexible sensor fusion platform. The deployed system targeted the influence of multiple sensors on 3D indoor location accuracy when faced with different-sized UAVs.…”
Section: B Contributionsmentioning
confidence: 99%
“…According to Lykou et al in [5], around 6% commercial UAV detection systems designed on acoustic sensors, 26% are using radio frequency (RF), 28% are radar-based, and 40% adopted visual sensors for detection. Mostly those sensors adopted for drone detection and classification are: radar (radio detection and ranging on several different frequency bands for both active and passive sensing) [6], cameras for the visible spectrum sensing [4], cameras detecting thermal or infrared (IR) emissions [7], LIDAR (light detection and ranging) [8], microphones/acoustic sensors for acoustic vibration detection [2], and RF [9], [10] monitoring sensors for the detection of radio signals [11].…”
Section: Introductionmentioning
confidence: 99%
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“…The distance between anchors and tags can be determined using two-way-ranging (TWR) [ 15 ]. Precise distance measurement enables accurate estimation of both 2D and 3D positions [ 16 , 17 , 18 ]. While the accuracy of TOA is generally superior among time-based methods, the latency of target positioning tends to increase with an increasing number of tags [ 19 ].…”
Section: Introductionmentioning
confidence: 99%