Localization of moving target using multilateration algorithm
Localization of targets is an essential function for ubiquitous automatic control utilized by computing systems. Numerous algorithms, Trilateration and Multilateration (MLAT) algorithm, have been developed to accommodate different systems for optimal performance in locating targets. In this thesis,...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2019
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| Online Access: | http://hdl.handle.net/10356/77605 |
| Summary: | Localization of targets is an essential function for ubiquitous automatic control utilized by computing systems. Numerous algorithms, Trilateration and Multilateration (MLAT) algorithm, have been developed to accommodate different systems for optimal performance in locating targets. In this thesis, we discuss and compare the contrasting methods of localization of moving target using data collected from bilateral gait analysis using the more precise algorithm, MLAT. These data are characterized through different regression analysis technique such as least square method, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). The results obtained are compared internally by Root Mean Square Error (RMSE) and computation time to determine the most optimal and efficient MLAT algorithm for bilateral gait analysis. |
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