A Real-Time Intelligent Wireless Mobile Station Location Estimator with Application to TETRA Network

Alotaibi, Faihan D.; Abdennour, Adel; Ali, Adel A.

doi:10.1109/tmc.2009.66

Cited by 2 publications

(2 citation statements)

References 45 publications

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“…Adopting TDOA as feature parameter can remove the nonsynchronous error of transmitter and receiver, and implement weighted matching to TDOA and RSSI vector, which Weakens the random effect of RSSI parameter. During the data gathering phase, the established characteristic parameter matrix shall include data of all grids to estimate the MS location [11]. Suppose that we have an MS located at position k and it receives signals from N APs, then its data matrix associated with its actual x-y coordinates is defined as…”

Section: Grid Characteristic Match Algorithmmentioning

confidence: 99%

An Indoor Location Algorithm Based on Grid Characteristic Match by TDOA-RSSI

Guan

Deng

et al. 2010

AMR

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According to indoor wireless environment and signal propagation model, an indoor location algorithm based on grid characteristics match by TDOA-RSSI combining is put forward in this paper, in which the RSSI and TDOA parameters are combined as grid characteristic parameters to calculate the weighted Euclidean distance. The location algorithm adopts KWNN algorithms for grid matching and location estimate. Simulation results show that this algorithm has better robustness and accuracy, and can effectively solve the problem of location estimates stability in general RSSI fingerprint location system.

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Section: Grid Characteristic Match Algorithmmentioning

confidence: 99%

An Indoor Location Algorithm Based on Grid Characteristic Match by TDOA-RSSI

Guan

Deng

et al. 2010

AMR

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show abstract

“…The literature review shows that a lot of analytical and experimental works have been done for radio propagation in mobile environment by using measurement as in [1,2]. There was study on propagation path loss in Malaysia environment [3] in sub-urban, jungle, open area and dense tree area and path loss exponent being compared with empirical model.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Hata Propagation Prediction Model in Suburban Area in Malaysia

Roslee¹,

Kwan²

2010

PIER C

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A Real-Time Intelligent Wireless Mobile Station Location Estimator with Application to TETRA Network

Cited by 2 publications

References 45 publications

An Indoor Location Algorithm Based on Grid Characteristic Match by TDOA-RSSI

An Indoor Location Algorithm Based on Grid Characteristic Match by TDOA-RSSI

Optimization of Hata Propagation Prediction Model in Suburban Area in Malaysia

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