Robust mobile location estimation based on signal attenuation for cellular communication systems

Lin, Ding‐Bing; Juang, Rong‐Terng; Lin, Hsin‐Piao

doi:10.1049/el:20046663

Cited by 10 publications

(6 citation statements)

References 4 publications

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“…Maximum likelihood (ML) [4], semi-definite relaxation (SDR) [5], centroid [6] and weighted least squares (WLS) [7,8,9] approaches are the common solutions for source localization using RSS measurements. It has been shown in [4] that the positioning accuracy of the ML methodology attains Cramér-Rao lower bound (CRLB) at sufficiently small noise conditions.…”

Section: Introductionmentioning

confidence: 99%

Accurate and simple source localization using differential received signal strength

Lin

Chan

2013

Digital Signal Processing

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Locating an unknown-position source using received signal strength (RSS) measurements in an accurate and low-complexity manner is addressed in this paper. Given that the source transmit power is unknown, we employ the differential RSS information to devise two computationally attractive localization methods based on the weighted least squares (WLS) approach. The main ingredients in the first algorithm development are to obtain the unbiased estimates of the squared ranges and introduce an extra variable. The second method improves the first version by implicitly exploiting the relationship between the extra variable and source location through a second WLS step. The performance of the two estimators is analyzed in the presence of zero-mean white Gaussian disturbances. Numerical examples are also included to evaluate their localization accuracy by comparing with the maximum likelihood approach and Cramér-Rao lower bound.

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Section: Introductionmentioning

confidence: 99%

Accurate and simple source localization using differential received signal strength

Lin

Chan

2013

Digital Signal Processing

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“…We proposed the idea of signal strength difference for mobile location in [27] and this idea has been recently used for indoor localization in [8]. SSD uses the difference of signal strengths received at the AP's as a location fingerprint, (6).…”

Section: Rf Localizationmentioning

confidence: 99%

“…To address the issue of device diversity in fingerprintingbased methods, creating fingerprint database using signal strength difference (SSD) is promising than absolute received signal strength. We proposed the idea of signal strength difference for mobile location in [27] and this idea has been recently used for indoor localization in [8]. SSD uses the difference of signal strengths received at the AP's as a location fingerprint, (6).…”

Section: Rf Localizationmentioning

confidence: 99%

Hybrid Indoor Human Localization System for Addressing the Issue of RSS Variation in Fingerprinting

Bitew

Hsiao

Lin

et al. 2015

International Journal of Distributed Sensor Networks

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Indoor localization is used in many applications like security, healthcare, location based services, and social networking. Fingerprinting-based methods are widely used for indoor localization. But received signal strength (RSS) variation due to device diversity and change of conditions in the localization environment (e.g., distribution of furniture, people presence and movement, and opening and closing of doors) induce a significant localization error. To overcome this, we propose a hybrid indoor localization system using radio frequency (RF) and pyroelectric infrared (PIR) sensors. Our localization system has two stages. In the first stage, the zone of the target person is identified by PIR sensors. In the second stage, we apply K-nearest neighbor (K-NN) algorithm to the fingerprints within the zone identified and estimate position. Zone based processing of fingerprints will exclude deviated fingerprints because of RSS variation. We proposed two localization methods: Proposed 1 and Proposed 2 which use signal strength difference (SSD) and RSS, respectively. Simulation results show that the 0.8-meter accuracy of Proposed 1 achieves 84% and Proposed 2 achieves 65%, while traditional fingerprinting and SSD are 46% and 28%, respectively.

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“…They propose the propagation modeling for signal strength in sector cell systems and shows that the estimation accuracy of sector cell system is superior to that of omni cell systems because the amount of information for location estimation has increased and that the error criterion of location estimation is reduced as the standard deviation is decreased or the number of BSs is increased. Lin et al (2005) proposes a mobile location scheme using weighted centroid method based on the ratios of distances between mobile and base stations derived from the differences of signal attenuations. The proposed method does not require perfect path loss and shadowing models, and is capable to be applied in existing systems without hardware modifications.…”

Section: Received Signal Strengthmentioning

confidence: 99%

“…SA between two stations can be expressed as (Lin et al, 2005) x Where A(dB)is the signal attenuation, k 1 , k 2 , k 3 and k 4 denote different constants in the same clutter type of environment, f is the carrier frequency, h b and h m are, respectively, the heights of BS and MS, n is the path loss exponent, and x is a zero-mean Gaussian random variable.…”

Section: Proposed Hybrid Locating Techniquementioning

confidence: 99%

Hybrid Algorithm for Locating Mobile Station in Cellular Network

Al-Ifan

Hamid

Othman

et al. 2009

2009 International Conference on Future Computer and Communication

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Robust mobile location estimation based on signal attenuation for cellular communication systems

Cited by 10 publications

References 4 publications

Accurate and simple source localization using differential received signal strength

Accurate and simple source localization using differential received signal strength

Hybrid Indoor Human Localization System for Addressing the Issue of RSS Variation in Fingerprinting

Hybrid Algorithm for Locating Mobile Station in Cellular Network

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