On the Joint Estimation of the RSS-Based Location and Path-loss Exponent

Salman, Naveed; Ghogho, Mounir; Kemp, Andrew H.

doi:10.1109/wcl.2012.121411.110059

Cited by 80 publications

(35 citation statements)

References 11 publications

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“…The localization performance is improved by adopting convex optimization techniques. In [26], the authors deal with RSSI-based localization in an unknown path loss model and the proposed method exhibits better performance at low signal-to-noise ratio. In [27], a weighed least squares (WLS) is derived to localize the target with unknown transmission power and path loss exponent.…”

Section: Introductionmentioning

confidence: 99%

A RSSI-based parameter tracking strategy for constrained position localization

Diouris

Wang

2017

EURASIP J. Adv. Signal Process.

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In this paper, a received signal strength indicator (RSSI)-based parameter tracking strategy for constrained position localization is proposed. To estimate channel model parameters, least mean squares method (LMS) is associated with the trilateration method. In the context of applications where the positions are constrained on a grid, a novel tracking strategy is proposed to determine the real position and obtain the actual parameters in the monitored region. Based on practical data acquired from a real localization system, an experimental channel model is constructed to provide RSSI values and verify the proposed tracking strategy. Quantitative criteria are given to guarantee the efficiency of the proposed tracking strategy by providing a trade-off between the grid resolution and parameter variation. The simulation results show a good behavior of the proposed tracking strategy in the presence of space-time variation of the propagation channel. Compared with the existing RSSI-based algorithms, the proposed tracking strategy exhibits better localization accuracy but consumes more calculation time. In addition, a tracking test is performed to validate the effectiveness of the proposed tracking strategy.

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Section: Introductionmentioning

confidence: 99%

A RSSI-based parameter tracking strategy for constrained position localization

Diouris

Wang

2017

EURASIP J. Adv. Signal Process.

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“…This was achieved through a measurement campaign consisting of a number of usage scenarios, in a 2-storey terrace house in Bristol, United Kingdom (UK). The received signal strength indicator (RSSI), which is conventionally used for localization [15][16][17][18] in indoor or outdoor environments and for the determination of the channel model that relates the received signal strength with the distance [19][20][21][22], is the measured parameter in this campaign.…”

Section: Introductionmentioning

confidence: 99%

Investigation into off-body links for wrist mounted antennas in bluetooth systems

Abdullah

Fafoutis

Mellios

et al. 2015

2015 Loughborough Antennas &Amp; Propagation Conference (LAPC)

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms Abstract-This paper presents a detailed investigation into off-body links for wrist mounted Bluetooth Low Energy (BLE) devices for an indoor environment and revolves around three low profile antennas (microstrip patch, printed monopole and external monopole). It studies the received signal strength across different usage scenarios and obstructions such as body shadow, wall and ceiling through measurement campaigns carried out in a 2-storey house. It is observed that RSSIs show little variation from the mean value at any position in a given room of the house. In the living room, the average RSSI for patch, printed and external monopole is close to -61,-73 and -61 dBm respectively. The study describes the effect of usual obstructions such as wall and ceiling to off-body links and shows that the range of RSSI for any antenna (30 dBm at P=0.5 for Patch Antenna) is bounded at one end by the CDF of wall plus body shadow and at the other end by CDF of Line of Sight (LOS). The effect of body shadowing is studied in greater detail. It is observed that the microstrip patch antenna in LOS, under a ceiling and behind a wall, drops by approximately 15dB, 5dB and 10dB at P=0.4 when it goes into body shadow. The study also suggests that the Access Point (AP) on the ceiling provides better off-body links as compared to it in the adjacent room. The study compares the overall performance of the three antennas across all possible usage scenarios, obstructions & polarizations and concludes that the external monopole and patch antenna performs better than printed monopole by approximately 10-13 dBm. Finally, the study shows the variation of Packet Error Rate (PER) with RSSI and determines threshold values of RSSI for acceptable PERs, for reliable and robust applications.

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“…Due to the non linear nature of the localization problem, location estimation via RSS (and also for ToA) can be achieved using maximum likelihood (ML) techniques [14], [15], [16] that commonly operate in an iterative fashion. Generally, a close initial estimate of location is required for the ML algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…The solution to (6) is obtained using high complexity iterative techniques such as the Gauss-Newton or LevenbergMarquardt techniques [15], [16]. Due to its iterative nature, the ML techniques can converge to local minimum instead of global minimum if given an initial seed that is far from the actual node location.…”

Section: Introductionmentioning

confidence: 99%

Optimized Low Complexity Sensor Node Positioning in Wireless Sensor Networks

2014

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Abstract-Localization of sensor nodes in wireless sensor networks (WSNs) promotes many new applications. Longer life time is imperative for WSNs, this requirement constrains the energy consumption and computation power of the nodes. In order to locate sensors at a low cost, the received signal strength (RSS)-based localization is favored by many researchers. RSS positioning does not require any additional hardware on the sensors and does not consume extra power. A low complexity solution to RSS localization is the linear least squares (LLS) method.In this paper, we analyze and improve the performance of this method. Firstly, a weighted least squares (WLS) algorithm is proposed which considerably improves the location estimation accuracy. Secondly, reference anchor optimization using a technique based on the minimization of the theoretical mean square error (MSE) is also proposed to further improve performance of LLS and WLS algorithms. Finally, in order to realistically bound the performance of any unbiased RSS location estimator based on the linear model, the linear Cramer-Rao bound (CRB) is derived. It is shown via simulations that employment of the optimal reference anchor selection technique considerably improves system performance, while the WLS algorithm pushes the estimation performance closer to the linear CRB. Finally, it is also shown that the linear CRB has larger error than the exact CRB, which is the expected outcome.

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On the Joint Estimation of the RSS-Based Location and Path-loss Exponent

Cited by 80 publications

References 11 publications

A RSSI-based parameter tracking strategy for constrained position localization

A RSSI-based parameter tracking strategy for constrained position localization

Investigation into off-body links for wrist mounted antennas in bluetooth systems

Optimized Low Complexity Sensor Node Positioning in Wireless Sensor Networks

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