A Survey on Radio Frequency based Precise Localisation Technology for UAV in GPS-denied Environment

Yang, Beiya; Yang, Erfu

doi:10.1007/s10846-021-01500-4

Cited by 35 publications

(31 citation statements)

References 106 publications

(188 reference statements)

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“…Indoor localization has been extensively studied for decades. Scholars have adopted various signals to develop related works, including ultra-wideband (UWB) [ 11 , 12 , 13 ], WIFI [ 14 , 15 , 16 ], Radio Frequency Identification (RFID) [ 17 , 18 ], Bluetooth [ 19 , 20 ], Geomagnetic sequence [ 21 , 22 ] and Ultrasonic signals [ 3 , 23 ]. Despite the accuracy in special trial sites, they have a few practical limitations that hinder their wide deployment.…”

Section: Related Workmentioning

confidence: 99%

A Low-Cost and Efficient Indoor Fusion Localization Method

Yan

Deng

et al. 2022

Sensors

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Accurate indoor location information has considerable social and economic value in applications, such as pedestrian heatmapping and indoor navigation. Ultrasonic-based approaches have received significant attention mainly since they have advantages in terms of positioning with temporal correlation. However, it is a great challenge to gain accurate indoor localization due to complex indoor environments such as non-uniform indoor facilities. To address this problem, we propose a fusion localization method in the indoor environment that integrates the localization information of inertial sensors and acoustic signals. Meanwhile, the threshold scheme is used to eliminate outliers during the positioning process. In this paper, the estimated location is fused by the adaptive distance weight for the time difference of arrival (TDOA) estimation and improved pedestrian dead reckoning (PDR) estimation. Three experimental scenes have been developed. The experimental results demonstrate that the proposed method has higher localization accuracy in determining the pedestrian location than the state-of-the-art methods. It resolves the problem of outliers in indoor acoustic signal localization and cumulative errors in inertial sensors. The proposed method achieves better performance in the trade-off between localization accuracy and low cost.

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Section: Related Workmentioning

confidence: 99%

A Low-Cost and Efficient Indoor Fusion Localization Method

Yan

Deng

et al. 2022

Sensors

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“…To overcome aforementioned issues, the ultra-wideband (UWB) based localisation technology becomes an ideal candidate, due to the centimetre-level ranging accuracy and reliable performance in different environments. Meanwhile, owing to the essential characteristics of the electromagnetic wave, the low visibility condition, feature-less issue and error accumulation can be ignored with the UWB based localisation technology [7], [12].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Extended Kalman Filter-Based Fusion Approach for High-Precision UAV Positioning in Extremely Confined Environments

Yang

et al. 2023

IEEE/ASME Trans. Mechatron.

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For unmanned aerial vehicle (UAV) based smart inspection in extremely confined environments, it is impossible for precise UAV positioning with global positioning system (GPS), owing to the satellite signal block. Therefore, the ultra-wideband (UWB) based technology has attracted extensive attention under such circumstances. However, due to the unpredictable propagation condition and the time-varying operational environment, the localisation performance oscillation caused by the changing measurement noise may lead to the instability of UAV. To mitigate the effects, in this paper, a high precision UAV positioning system which integrates the inertial measurement unit (IMU) and UWB with the adaptive extended Kalman filter (AEKF) is proposed. Compared with the traditional EKF based approach, the estimated and recorded information from previous processes is exploited to adaptively estimate and further control the estimation of the noise covariance matrices for performance improvement. Finally, simulations and experiments have been conducted in extremely confined environments. According to the results, the proposed algorithm can significantly improve the position update rate, the median positioning error, the 95 th percentile positioning error and the average standard deviation (STD) into 88Hz, 0.102m, 0.192m and 0.052m, which is applicable for applications in focused environments.Index Terms-Unmanned aerial vehicle (UAV), adaptive extended Kalman filter (AEKF), ultra-wideband (UWB), inertial measurement unit (IMU), sensor fusion, extremely confined environments.

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“…Since communication with the satellite network is partially or completely impractical in any indoor environment, for the UAVs acting in these contexts, other sources of position information are necessary, such as acoustic [ 18 ], radio frequency [ 19 ] signals, visible light communication [ 20 ], vision systems [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Indoor Visual-Based Localization System for Multi-Rotor UAVs

Bertoni

Michieletto

Oboe

et al. 2022

Sensors

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Industry 4.0, smart homes, and the Internet of Things are boosting the employment of autonomous aerial vehicles in indoor environments, where localization is still challenging, especially in the case of close and cluttered areas. In this paper, we propose a Visual Inertial Odometry localization method based on fiducial markers. Our approach enables multi-rotor aerial vehicle navigation in indoor environments and tackles the most challenging aspects of image-based indoor localization. In particular, we focus on a proper and continuous pose estimation, working from take-off to landing, at several different flying altitudes. With this aim, we designed a map of fiducial markers that produces results that are both dense and heterogeneous. Narrowly placed tags lead to minimal information loss during rapid aerial movements while four different classes of marker size provide consistency when the camera zooms in or out according to the vehicle distance from the ground. We have validated our approach by comparing the output of the localization algorithm with the ground-truth information collected through an optoelectronic motion capture system, using two different platforms in different flying conditions. The results show that error mean and standard deviation can remain constantly lower than 0,11m, so not degrading when the aerial vehicle increases its altitude and, therefore, strongly improving similar state-of-the-art solutions.

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A Survey on Radio Frequency based Precise Localisation Technology for UAV in GPS-denied Environment

Cited by 35 publications

References 106 publications

A Low-Cost and Efficient Indoor Fusion Localization Method

A Low-Cost and Efficient Indoor Fusion Localization Method

Adaptive Extended Kalman Filter-Based Fusion Approach for High-Precision UAV Positioning in Extremely Confined Environments

Indoor Visual-Based Localization System for Multi-Rotor UAVs

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