Two Efficient and Easy-to-Use NLOS Mitigation Solutions to Indoor 3-D AOA-Based Localization

Xiong, Wenxin; Bordoy, Joan; Gabbrielli, Andrea; Fischer, Georg; Schott, Dominik Jan; Höflinger, Fabian; Wendeberg, Johannes; Schindelhauer, Christian; Rupitsch, Stefan J.

doi:10.1109/ipin51156.2021.9662529

Cited by 7 publications

(4 citation statements)

References 23 publications

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“…MVG, KF, and EKF are deterministic approaches that are widely used to reduce noise and interference effects on UWB measurements. However, in NLOS scenarios where UWB signals are obstructed by obstacles and reflect from multiple paths [ 10 , 11 , 12 ], these algorithms may not perform well.…”

Section: Related Workmentioning

confidence: 99%

Comparative Analysis of Integrated Filtering Methods Using UWB Localization in Indoor Environment

Ranjan,

Shin,

Jung

et al. 2024

Sensors

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This research delves into advancing an ultra-wideband (UWB) localization system through the integration of filtering technologies (moving average (MVG), Kalman filter (KF), extended Kalman filter (EKF)) with a low-pass filter (LPF). We investigated new approaches to enhance the precision and reduce noise of the current filtering methods—MVG, KF, and EKF. Using a TurtleBot robotic platform with a camera, our research thoroughly examines the UWB system in various trajectory situations (square, circular, and free paths with 2 m, 2.2 m, and 5 m distances). Particularly in the square path trajectory with the lowest root mean square error (RMSE) values (40.22 mm on the X axis, and 78.71 mm on the Y axis), the extended Kalman filter with low-pass filter (EKF + LPF) shows notable accuracy. This filter stands out among the others. Furthermore, we find that integrated method using LPF outperforms MVG, KF, and EKF consistently, reducing the mean absolute error (MAE) to 3.39% for square paths, 4.21% for circular paths, and 6.16% for free paths. This study highlights the effectiveness of EKF + LPF for accurate indoor localization for UWB systems.

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Section: Related Workmentioning

confidence: 99%

Comparative Analysis of Integrated Filtering Methods Using UWB Localization in Indoor Environment

Ranjan,

Shin,

Jung

et al. 2024

Sensors

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“…This is essential to support the application-driven research and development of ILS, increase market transparency, thus, advancing the practical application of ILS. [83] Magnetic Reference System Hall Two Efficient and Easy-to-Use NLOS Mitigation Solutions to Indoor 3-D AOA-Based Localization [84] Acoustic Other Hall POUCET: A Multi-Technology Indoor Positioning Solution for Firefighters and Soldiers [85] Multiple Other Mixed Adaptive procedure for indoor localization using LoRa devices [86] RF Other Hall Multidimensional In-and Outdoor Pedestrian Tracking using OpenStreetMap Data [87] Multiple Other Building Indoor Localization Method For a Microphone Using a Single Speaker [88] Acoustic…”

Section: Different Limitation Exist (1)mentioning

confidence: 99%

Meaningful Test & Evaluation of Indoor Localization Systems in Semi-Controlled Environments

Schyga¹,

Hinckeldeyn²,

Kreutzfeldt³

2022

Preprint

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Despite their enormous potential the use of Indoor Localization Systems (ILS) remains 1 seldom. One reason is the lack of market transparency and stakeholders’ trust in the systems’ 2 performance as a consequence of insufficient use of Test and Evaluation (T&E) methodologies. The 3 heterogeneous nature of ILS, their influences, and their applications pose various challenges for 4 the design of a methodology that provides meaningful results. Methodologies for building-wide 5 testing exist, but their use is mostly limited to associated indoor localization competitions. In this 6 work, the T&E 4iLoc Framework is proposed - a methodology for T&E of indoor localization systems 7 in semi-controlled environments based on a system-level and black-box approach. In contrast to 8 building-wide testing, T&E in semi-controlled environments, such as test halls is characterized by 9 lower costs, higher reproducibility, and better comparability of the results. The limitation of low 10 transferability to real world applications is addressed by an application-driven design approach. 11 The empirical validation of the T&E 4iLoc Framework, based on the examination of a contour-based 12 Light Detection and Ranging ILS, an Ultra Wideband ILS, and a camera-based ILS for the application 13 of Automated Guided Vehicles in warehouse operation, demonstrates the benefits of T&E with the 14 T&E 4iLoc Framework.

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“…One of the typical methods is outlier detection, which eliminates suspicious outlier data in the measured data. A weighted linear least squares estimator is derived for the line of sight (LOS) AOA component in terms of the direction-of-arrival vector, and then a data selection method is performed using the sum of squared residuals to discard error-prone NLOS connections [ 26 ]. A Bayesian sequence test is first used to distinguish between the line of sight ( LOS ) or NLOS conditions.…”

Section: Related Workmentioning

confidence: 99%

“…There are two traditional methods to handle outlier problems: outlier detection and robust estimator. Outlier detection refers to detecting suspected outliers and separating them from the original data set, then using the remaining data to complete the localization [ 26 , 27 , 28 ]. Although the outlier detection method is intuitive and effective, it is not suitable for large data sets or complex application scenarios.…”

Section: Introductionmentioning

confidence: 99%

Robust AOA-Based Target Localization for Uniformly Distributed Noise via ℓp-ℓ1 Optimization

Chen

Wang

Yan

2022

Entropy

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This paper addresses the problem of robust angle of arrival (AOA) target localization in the presence of uniformly distributed noise which is modeled as the mixture of Laplacian distribution and uniform distribution. Motivated by the distribution of noise, we develop a localization model by using the ℓp-norm with 0≤p<2 as the measurement error and the ℓ1-norm as the regularization term. Then, an estimator for introducing the proximal operator into the framework of the alternating direction method of multipliers (POADMM) is derived to solve the convex optimization problem when 1≤p<2. However, when 0≤p<1, the corresponding optimization problem is nonconvex and nonsmoothed. To derive a convergent method for this nonconvex and nonsmooth target localization problem, we propose a smoothed POADMM estimator (SPOADMM) by introducing the smoothing strategy into the optimization model. Eventually, the proposed algorithms are compared with some state-of-the-art robust algorithms via numerical simulations, and their effectiveness in uniformly distributed noise is discussed from the perspective of root-mean-squared error (RMSE). The experimental results verify that the proposed method has more robustness against outliers and is less sensitive to the selected parameters, especially the variance of the measurement noise.

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Two Efficient and Easy-to-Use NLOS Mitigation Solutions to Indoor 3-D AOA-Based Localization

Cited by 7 publications

References 23 publications

Comparative Analysis of Integrated Filtering Methods Using UWB Localization in Indoor Environment

Comparative Analysis of Integrated Filtering Methods Using UWB Localization in Indoor Environment

Meaningful Test & Evaluation of Indoor Localization Systems in Semi-Controlled Environments

Robust AOA-Based Target Localization for Uniformly Distributed Noise via ℓp-ℓ1 Optimization

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