A non-line-of-sight error mitigation algorithm in location estimation

Chen, Pi-Chun

doi:10.1109/wcnc.1999.797838

Cited by 290 publications

(33 citation statements)

References 4 publications

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“…From the simulation results shown in Figures 8, 9, 10, and 11, the proposed IMM-EKF smoother can more accurately track the true range distances in indoor LOS/NLOS mixed situations. The main reason lies in that the mean noise error is introduced into the weighted fusion estimation at the stage of ranging filter, as shown in Equation (26). At the same time, the EKF algorithm goes a step further to depress the localization error.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

“…In [25], a linear programming (LP) approach is adopted for NLOS mitigation. Some researchers propose soft-decision algorithms without NLOS identification and discarding [26][27][28]. In [26,27], Chen uses a residual weighting (RWgh)-based algorithm to alleviate the NLOS errors.…”

Section: Related Workmentioning

confidence: 99%

“…Some researchers propose soft-decision algorithms without NLOS identification and discarding [26][27][28]. In [26,27], Chen uses a residual weighting (RWgh)-based algorithm to alleviate the NLOS errors. On the basis of Chen's research, Hammes and Zoubir [28] suggest a data fusion algorithm to achieve higher localization accuracy.…”

Section: Related Workmentioning

confidence: 99%

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Moving target localization in indoor wireless sensor networks mixed with LOS/NLOS situations

Zhang

Wei

et al. 2013

J Wireless Com Network

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Indoor target localization is an essential and fundamental issue for wireless sensor networks (WSN). However, it is rather difficult for WSN to maintain the localization accuracy in line-of-sight (LOS) and non-line-of-sight (NLOS) mixed environment. NLOS propagation always leads to larger ranging error than LOS does. When the target moves in the rooms and corridors, the signal transmission state will switch frequently between LOS and NLOS. It is a challenging task to deal with this situation because the ranging error characteristics under LOS and NLOS conditions are quite different. In this paper, we propose an interacting multiple model-extended Kalman filter (IMM-EKF) algorithm to improve the localization accuracy for moving target in indoor environment. In the IMM structure, two Kalman filters (KF) are adopted in parallel to accurately smoothen the distance measurement. The proposed algorithm can adapt to the dynamically changing condition between LOS and NLOS due to the two KFs' interaction so that large NLOS ranging errors are further reduced. Once the estimated ranges are obtained, the EKF is employed to estimate the target's location. Empirical measurement results are obtained from typical office environment to verify the effectiveness of the proposed algorithm. Experimental results illustrate that the IMM smoother can efficiently mitigate the NLOS effects on ranging errors and achieve high localization accuracy.

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Section: Experimental Results and Analysismentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Moving target localization in indoor wireless sensor networks mixed with LOS/NLOS situations

Zhang

Wei

et al. 2013

J Wireless Com Network

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“…In the simulation, we study two cases for the measurement noise: (1) all measurements are positive and (2) measurements noise can be both positive and negative. For positive measurement errors, we use an exponential distribution [47]:…”

Section: Simulation Resultsmentioning

confidence: 99%

Wireless network positioning as a convex feasibility problem

Gholami

Wymeersch

Ström

et al. 2011

J Wireless Com Network

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In this semi-tutorial paper, the positioning problem is formulated as a convex feasibility problem (CFP). To solve the CFP for non-cooperative networks, we consider the well-known projection onto convex sets (POCS) technique and study its properties for positioning. We also study outer-approximation (OA) methods to solve CFP problems. We then show how the POCS estimate can be upper bounded by solving a non-convex optimization problem. Moreover, we introduce two techniques based on OA and POCS to solve the CFP for cooperative networks and obtain two new distributed algorithms. Simulation results show that the proposed algorithms are robust against non-line-of-sight conditions.

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“…Range errors take into account the measurements errors resulted from channel noise, and NLOS errors resulted from blocks presence in the direct path [63]. Thus, Eq.…”

Section: Refinement Geolocation Techniquesmentioning

confidence: 99%

Taxonomy of Fundamental Concepts of Localization in Cyber-Physical and Sensor Networks

Koubâa

Jamâa²

2013

Wireless Pers Commun

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Localization is a fundamental task in Cyber-Physical Systems (CPS), where data is tightly coupled with the environment and the location where it is generated. The research literature on localization has reached a critical mass, and several surveys have also emerged. This review paper contributes on the state-of-the-art with the proposal of a new and holistic taxonomy of the fundamental concepts of localization in CPS, based on a comprehensive analysis of previous research works and surveys. The main objective is to pave the way towards a deep understanding of the main localization techniques, and unify their descriptions. Furthermore, this review paper provides a complete overview on the most relevant localization and geolocation techniques. Also, we present the most important metrics for measuring the accuracy of localization approaches, which is meant to be the gap between the real location and its estimate. Finally, we present open issues and research challenges pertaining to localization. We believe that this review paper will represent an important and complete reference of localization techniques in CPS for researchers and practitioners and will provide them with an added value as compared to previous surveys.

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A non-line-of-sight error mitigation algorithm in location estimation

Cited by 290 publications

References 4 publications

Moving target localization in indoor wireless sensor networks mixed with LOS/NLOS situations

Moving target localization in indoor wireless sensor networks mixed with LOS/NLOS situations

Wireless network positioning as a convex feasibility problem

Taxonomy of Fundamental Concepts of Localization in Cyber-Physical and Sensor Networks

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