Location using LOS range estimation in NLOS environments

Venkatraman, S.; Caffery, J.; You, Hojun

doi:10.1109/vtc.2002.1002609

Cited by 71 publications

(51 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The produced array outputs are then orthogonal or nearly orthogonal. In matrix notation, the output of the array is (10) where X is the incident signal (11) and is the matrix of the spreading sequences (12). (11) (12)…”

Section: Sdma Algorithmmentioning

confidence: 99%

Passive Source Localization in a Randomly Distributed Wireless Sensor Networks

Niaz¹,

Khan²,

Shafi³

2011

IJCA

View full text Add to dashboard Cite

This paper proposes a source localization scheme using random arrays of Wireless Sensor Networks (WSN). A Total Least Square (TLS) estimator is proposed which improves the result of the location of source node. Using a relatively new Direction of Arrival (DOA) estimation technique Space Division Multiple Access (SDMA) receiver the proposed solution is able to perform localization in a multipath environment. The propose scheme considers both Line of Sight (LOS) and Non Line of Sight (NLOS) signals to perform the localization with the TLS estimator which is efficient than a simple Least Square (LS) estimator. Simulation results are included to demonstrate that the proposed solution provides an improved estimate by exploiting the NLOS information, SDMA receiver and using TLS estimator.

show abstract

Section: Sdma Algorithmmentioning

confidence: 99%

Passive Source Localization in a Randomly Distributed Wireless Sensor Networks

Niaz¹,

Khan²,

Shafi³

2011

IJCA

View full text Add to dashboard Cite

show abstract

“…It was motivated by the requirement put forth by Federal Communications Commission (FCC) to cellular operators to be able to locate a mobile handset within an accuracy of 300 meters for 95% of calls [13]. In current literature [14,15,16,17,18,19,20,21] there are three general methods to deal with NLOS readings. The first method attempts to identify and use only LOS measurements.…”

Section: Localization In Cluttered Underwater Environmentsmentioning

confidence: 99%

“…The second method incorporates both LOS and NLOS distance measurements with appropriate weighting to minimize the contribution of NLOS observations. Here the primary assumption made is that the number of LOS readings is much greater than the number of NLOS readings [16,17], which may not be the case in our underwater cluttered environment. The third method advocates the use of scattering models.…”

Section: Localization In Cluttered Underwater Environmentsmentioning

confidence: 99%

An Underwater Robotic Network for Monitoring Nuclear Waste Storage Pools

Nawaz

Hussain

Watson

et al. 2010

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

View full text Add to dashboard Cite

Abstract. Nuclear power provides a significant portion of our current energy demand and is likely to become more wide spread with growing world population. However, the radioactive waste generated in these power plants must be stored for around 60 years in underwater storage pools before permanent disposal. These underwater storage environments must be carefully monitored and controlled to avoid an environmental catastrophe. In this paper, we present an underwater mobile sensor network that is being developed to monitor these waste storage pools. This sensing system will also be used in very old storage pools to build maps of their internal structure which can then be used for waste removal and pool decommissioning. In this paper, we outline the unique challenges of our application scenario which include robot localization in cluttered underwater environments and the effect of location errors on environment mapping. We also list other industrial applications that can benefit from our underwater sensor network.

show abstract

“…Various NLOS mitigation techniques have emerged [12,19,[29][30][31][32][33][34] to overcome this problem. The two emerged mitigation techniques are classified as follows: the first is called residual weighting [12,[29][30][31]; the second is the LOS reference devices identification methodology [19,[32][33][34]. The first mitigation technique attempts to minimize the contribution of the NLOS multipaths, leaving the unanswered questions of about its overall mitigation technique reliability.…”

Section: Introductionmentioning

confidence: 99%

Localization of Omni-Directional Mobile Device in Multipath Environments

Seow¹,

Tan²

2008

PIER

View full text Add to dashboard Cite

Abstract-This paper presents a comprehensive Non Line of Sight (NLOS) localization scheme in a multipath environment where the scatterers with smooth surfaces are aligned parallel or perpendicular to each other. It leverages on the estimation of Angle of Arrival (AOA) and Time of Arrival (TOA) of the omni-directional mobile device's signal received at the reference devices. Unlike the conventional Line of Sight (LOS) localization schemes that rely on the various mitigation techniques to mitigate the multipaths that are mistaken as the LOS signal, our proposed two step localization scheme not only utilizes the LOS path but also any one bound scattering NLOS multipath arriving at the reference devices for localization. Channel experiment coupled with simulation results in a typical multipath environment has demonstrated that our proposed localization scheme outperforms the conventional localization schemes that are coupled with their own mitigation techniques. Robustness in performance of our proposed localization scheme towards different scatterers' orientation where they are not aligned parallel or perpendicular to each other are also investigated.

show abstract

Location using LOS range estimation in NLOS environments

Cited by 71 publications

References 7 publications

Passive Source Localization in a Randomly Distributed Wireless Sensor Networks

Passive Source Localization in a Randomly Distributed Wireless Sensor Networks

An Underwater Robotic Network for Monitoring Nuclear Waste Storage Pools

Localization of Omni-Directional Mobile Device in Multipath Environments

Contact Info

Product

Resources

About