Location management scheme with WLAN positioning algorithm for integrated wireless networks

Tseng, Chih-Hsiung; Cheng, Sheng-Tzong

doi:10.1016/j.comcom.2008.07.007

Cited by 5 publications

(2 citation statements)

References 25 publications

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“…Other techniques such as the Gaussian mixture model via expectation -maximization algorithm (EM) were also applied 17 . Assuming that all APs are independent…”

Section: Conventional Wlan Positioning Algorithmsmentioning

confidence: 99%

A signal strength priority based position estimation for mobile platforms

2010

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Global Positioning System (GPS) products help to navigate while driving, hiking, boating, and flying. GPS uses a combination of orbiting satellites to determine position coordinates. This works great in most outdoor areas, but the satellite signals are not strong enough to penetrate inside most indoor environments. As a result, a new strain of indoor positioning technologies that make use of 802.11 wireless LANs (WLAN) is beginning to appear on the market. In WLAN positioning the system either monitors propagation delays between wireless access points and wireless device users to apply trilateration techniques or it maintains the database of location-specific signal fingerprints which is used to identify the most likely match of incoming signal data with those preliminary surveyed and saved in the database. In this paper we investigate the issue of deploying WLAN positioning software on mobile platforms with typically limited computational resources. We suggest a novel received signal strength rank order based location estimation system to reduce computational loads with a robust performance. The proposed system performance is compared to conventional approaches.

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“…Other techniques such as the Gaussian mixture model via expectation -maximization algorithm (EM) were also applied 17 . Assuming that all APs are independent…”

Section: Conventional Wlan Positioning Algorithmsmentioning

confidence: 99%

A signal strength priority based position estimation for mobile platforms

2010

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“…Range-free localization methods do not use physical parameters but work with the content of a message and are also not treated here. There are different technologies used for indoor localization: ultrasonic [10], infrared [11], Bluetooth [12], RFID [11,12], WiFi [13,14], UWB [15][16][17], and a combination of technologies [18,19]. These technologies all have not only their respective advantages, but also shortcomings.…”

Section: Related Workmentioning

confidence: 99%

Automated linear regression tools improve RSSI WSN localization in multipath indoor environment

Vanheel

Verhaevert

Laermans

et al. 2011

J Wireless Com Network

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Received signal strength indication (RSSI)-based localization is emerging in wireless sensor networks (WSNs). Localization algorithms need to include the physical and hardware limitations of RSSI measurements in order to give more accurate results in dynamic real-life indoor environments. In this study, we use the Interdisciplinary Institute for Broadband Technology real-life test bed and present an automated method to optimize and calibrate the experimental data before offering them to a positioning engine. In a preprocessing localization step, we introduce a new method to provide bounds for the range, thereby further improving the accuracy of our simple and fast 2D localization algorithm based on corrected distance circles. A maximum likelihood algorithm with a mean square error cost function has a higher position error median than our algorithm. Our experiments further show that the complete proposed algorithm eliminates outliers and avoids any manual calibration procedure.

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An Indoor Positioning Algorithm with Kernel Direct Discriminant Analysis

Deng

Meng

2010

2010 IEEE Global Telecommunications Conference GLOBECOM 2010

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Location management scheme with WLAN positioning algorithm for integrated wireless networks

Cited by 5 publications

References 25 publications

A signal strength priority based position estimation for mobile platforms

A signal strength priority based position estimation for mobile platforms

Automated linear regression tools improve RSSI WSN localization in multipath indoor environment

An Indoor Positioning Algorithm with Kernel Direct Discriminant Analysis

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