Entropy-based non-line of sight identification for wireless positioning systems

2014 ◽  
Author(s):  
Nayef Alsindi ◽  
Zdenek Chaloupka ◽  
James Aweya
Keyword(s):  
Line Of Sight ◽  
Positioning Systems ◽  
Wireless Positioning ◽  
Non Line Of Sight

scholarly journals Multipath Map Method for TDOA Based Indoor Reverse Positioning System with Improved Chan-Taylor Algorithm

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3223 ◽  
Author(s):  
Cheng Hua ◽  
Kun Zhao ◽  
Danan Dong ◽  
Zhengqi Zheng ◽  
Chao Yu ◽  
...  
Keyword(s):  
Iterative Algorithm ◽  
Line Of Sight ◽  
Positioning System ◽  
Domain Modeling ◽  
Time Difference Of Arrival ◽  
Arrival Times ◽  
Positioning Systems ◽  
Negative Effect ◽  
Height Component ◽  
Non Line Of Sight

We study wireless indoor positioning systems where multiple synchronized infrastructure devices simultaneously receive signals from an object of interest whose arrival times are measured. The positioning performance is degraded by unresolvable channel multipath and non-line-of-sight (NLOS) reflctions which cause a bias in the time difference of arrival (TDOA) measurements. In order to reduce the negative effect of multi-path, a Multi-Path Map (MPM) method based on spatial domain modeling principle in the reverse positioning framework with good robustness is proposed. Meanwhile, an improved non-linear iterative algorithm with height component constrained which reduces the complexity is introduced to calculate the coordinates so that the performance of the MPM can be verified. By using the MPM measurements as pre-calibration information to compensate the TDOA observed value, the accuracy of the cooperative location based on a UWB device is 6.45 cm, which achieves 63% improvement than that of none MPM used.

scholarly journals Robustly Adaptive EKF PDR/UWB Integrated Navigation Based on Additional Heading Constraint

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4390
Author(s):  
Debao Yuan ◽  
Jian Zhang ◽  
Jian Wang ◽  
Ximin Cui ◽  
Fei Liu ◽  
...  
Keyword(s):  
Dead Reckoning ◽  
Wide Band ◽  
Satellite System ◽  
Line Of Sight ◽  
Indoor Environments ◽  
Integrated Navigation ◽  
Position Information ◽  
Positioning Systems ◽  
Global Navigation Satellite ◽  
Non Line Of Sight

At present, GNSS (Global Navigation Satellite System) positioning technology is widely used for outdoor positioning services because of its high-precision positioning characteristics. However, in indoor environments, effective position information cannot be provided, because of the signals being obscured. In order to improve the accuracy and continuity of indoor positioning systems, in this paper, we propose a PDR/UWB (Pedestrian Dead Reckoning and Ultra Wide Band) integrated navigation algorithm based on an adaptively robust EKF (Extended Kalman Filter) to address the problem of error accumulation in the PDR algorithm and gross errors in the location results of the UWB in non-line-of-sight scenarios. First, the basic principles of UWB and PDR location algorithms are given. Then, we propose a loose combination of the PDR and UWB algorithms by using the adaptively robust EKF. By using the robust factor to adjust the weight of the observation value to resist the influence of the gross error, and by adjusting the variance of the system adaptively according to the positioning scene, the algorithm can improve the robustness and heading factor of the PDR algorithm, which is constrained by indoor maps. Finally, the effectiveness of the algorithm is verified by the measured data. The experimental results showed that the algorithm can not only reduce the accumulation of PDR errors, but can also resist the influence of gross location errors under non-line-of-sight UWB scenarios.

Ultra Wideband Indoor Positioning Using Kalman Filters

2012 ◽  
Vol 433-440 ◽  
pp. 4207-4213 ◽  
Author(s):  
Li Zhang ◽  
Hao Zhang ◽  
Xue Rong Cui ◽  
T Aaron Gulliver
Keyword(s):  
Kalman Filter ◽  
Ultra Wideband ◽  
Line Of Sight ◽  
Time Difference Of Arrival ◽  
Positioning Systems ◽  
Positioning Technique ◽  
Performance Results ◽  
Source Of Error ◽  
Mitigation Technique ◽  
Non Line Of Sight

A time-difference-of-arrival (TDOA) positioning technique for indoor ultra wideband (UWB) systems is presented. Non-line-of-sight (NLOS) propagation error is a major source of error in positioning systems. Therefore an NLOS mitigation technique employing a Kalman filter is utilized to reduce the NLOS errors in indoor UWB environments. An extended Kalman filter (EKF) is used to process the TDOA data for mobile positioning and tracking. Performance results are presented which show that the proposed scheme can significantly improve the positioning accuracy in a UWB environment.

Integrating the Non-Line of Sight Launching System (NLOS-LS) in the United States Navy

2007 ◽  
Author(s):  
Jonathon Emis ◽  
Bryan Huang ◽  
Timothy Jones ◽  
Mei Li ◽  
Don Tumbocon
Keyword(s):  
United States ◽  
United States Navy ◽  
The United States ◽  
Line Of Sight ◽  
Non Line Of Sight

scholarly journals Low-cost SPAD sensing for non-line-of-sight tracking, material classification and depth imaging

2021 ◽  
Vol 40 (4) ◽  
pp. 1-12
Author(s):  
Clara Callenberg ◽  
Zheng Shi ◽  
Felix Heide ◽  
Matthias B. Hullin
Keyword(s):  
Low Cost ◽  
Line Of Sight ◽  
Depth Imaging ◽  
Material Classification ◽  
Non Line Of Sight

scholarly journals Target Localization via Integrated and Segregated Ranging Based on RSS and TOA Measurements

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 230 ◽  
Author(s):  
Slavisa Tomic ◽  
Marko Beko
Keyword(s):  
State Of The Art ◽  
Hybrid Approach ◽  
Critical Distance ◽  
Heuristic Approach ◽  
Target Localization ◽  
Line Of Sight ◽  
Time Of Arrival ◽  
Individual Measurement ◽  
New Approach ◽  
Non Line Of Sight

This work addresses the problem of target localization in adverse non-line-of-sight (NLOS) environments by using received signal strength (RSS) and time of arrival (TOA) measurements. It is inspired by a recently published work in which authors discuss about a critical distance below and above which employing combined RSS-TOA measurements is inferior to employing RSS-only and TOA-only measurements, respectively. Here, we revise state-of-the-art estimators for the considered target localization problem and study their performance against their counterparts that employ each individual measurement exclusively. It is shown that the hybrid approach is not the best one by default. Thus, we propose a simple heuristic approach to choose the best measurement for each link, and we show that it can enhance the performance of an estimator. The new approach implicitly relies on the concept of the critical distance, but does not assume certain link parameters as given. Our simulations corroborate with findings available in the literature for line-of-sight (LOS) to a certain extent, but they indicate that more work is required for NLOS environments. Moreover, they show that the heuristic approach works well, matching or even improving the performance of the best fixed choice in all considered scenarios.

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