研究目的
To analyze the performance of OBRIP and TRIP algorithms in an indoor optical wireless channel, optimize system parameters, and develop a mathematical model for positioning error.
研究成果
The TRIP algorithm outperforms OBRIP, reducing position estimation error by up to 30%, with minimum average errors of 0.61 m for TRIP and 0.81 m for OBRIP. The algorithms are robust to receiver tilting and parameter variations. A mathematical model based on raw moments provides closed-form expressions for standard deviation, confirming simulation results. The study offers guidelines for installing OWC-based IPS with optimal parameter values for sub-meter accuracy.
研究不足
The study assumes a line-of-sight configuration and does not consider non-line-of-sight effects or multipath interference. The mathematical model for overlapping circular beams is complex and may not scale perfectly for more than two LEDs. Room scaling is only validated for square rooms, and the effect of height is not fully addressed.
1:Experimental Design and Method Selection:
The study uses simulation-based performance analysis of OBRIP and TRIP algorithms in a 10 m × 10 m × 3 m room with a 3×3 LED array. A line-of-sight optical wireless channel model is employed, and mathematical modeling based on raw moments is used for validation.
2:Sample Selection and Data Sources:
25,000 randomly generated and uniformly distributed positions of an object at 1 m height are used for error calculations.
3:List of Experimental Equipment and Materials:
LEDs, optical receivers, optical filters, concentrators, and simulation software (not specified by brand or model).
4:Experimental Procedures and Operational Workflow:
Simulations vary parameters like beam radius (
5:25 m to 8 m), LED separation distance (5 m to 5 m), receiver tilting angle (-25° to 25°), and receiver separation distance (25 m to 5 m). Performance metrics include root mean square error (RMSE) and 90th percentile error from CDF plots. Data Analysis Methods:
Statistical analysis using RMSE calculation, CDF plots, and mathematical derivations for standard deviation.
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