## 5 Results and Discussion
\begin{table}
\begin{tabular}{c c c c c} \hline
**Simulation Param** & **Param** & **Scenario 1** & **Scenario 2** & **Scenario 3** \\ \hline \multirow{4}{*}{Emitter 1 (LED 1)} & Position (x, y, z) m & (3, 1, 5) & (1, 1, 5) & (1, 1, 5) \\  & Frequency (MHz) & 3.5 & 3.5 & 3.5 \\  & Mode (n) & 1 & 1 & 1 \\  & Semi Angle & 65\({}^{\circ}\) & 65\({}^{\circ}\) & 65\({}^{\circ}\) \\ \hline \multirow{4}{*}{Emitter 2 (LED 2)} & Position (x, y, z) m & (1, 3, 5) & (4, 1, 5) & (4, 1, 5) \\  & Frequency (MHz) & 8.5 & 8.5 & 8.5 \\  & Mode (n) & 1 & 1 & 1 \\  & Semi Angle & 65\({}^{\circ}\) & 65\({}^{\circ}\) & 65\({}^{\circ}\) \\ \hline \multirow{4}{*}{Emitter 3 (LED 3)} & Position (x, y, z) m & (4, 3, 5) & (3, 4, 5) & (3, 4, 5) \\  & Frequency (MHz) & 13.5 & 13.5 & 13.5 \\  & Mode (n) & 1 & 1 & 1 \\  & Semi Angle & 65\({}^{\circ}\) & 65\({}^{\circ}\) & 65\({}^{\circ}\) \\ \hline \multirow{4}{*}{Receiver (photodetector)} & Position (x, y, z) m & (4.5, 1.5, 3.2) & (2.5, 2.5, 2) & (1.8, 2, 3.5) \\  & Active area, cm\({}^{2}\) & 1.2 & 1.2 & 1.2 \\  & Field of View (FOV) & 65\({}^{\circ}\) & 65\({}^{\circ}\) & 65\({}^{\circ}\) \\ \hline \multicolumn{4}{c}{**Average Error (cm)**} & **16.4** & **10.6** & **3.5** \\ \hline \end{tabular}
\end{table} 
Table 1: System simulation parameters. As seen in Table 1, there are three scenarios in the simulation. In the first scenario, the location of the photodetector is selected in a corner and it is far away from the LEDs. It receives enough power just from one LED, but does not receive enough power from the two other LEDs. This generates a large localization estimation error equal to (16.4 cm). This is the averaged error value for 100 algorithm repetitions. The second scenario is related to the photodetector position closer to two LEDs and far away from the third LED. Then, it receives enough power from two LEDs and less power from the other LED. The averaged localization error is better than the first scenario, and it is equal to (10.6 cm). The last scenario is for the photodetector exactly located behind and close to the three LEDs; hence, the photodetector receives enough power from the three LEDs. Therefore, the estimated spheres and \(d\) param are more accurate and the localization error is better than the two other scenarios. The averaged localization error is dependent on the power emitted by the LED, and by the distance between LEDs and photodetector. For the cases when the photodetector is far away from the LEDs, then it receives less power and the localization error is high. But for the condition in which the photodetector is closer to the LEDs, it receives more power and the localization error is lower. Figure 5 shows the intersection between these three spheres for the evaluated scenarios. This figure has been plotted for three scenarios. Also, the intersection between three spheres is specified in this figure. As seen, when the photodetector place is far from the LEDs position, the estimated location is farther away from the real location. When the photodetector is closer to the LEDs, the real and estimated locations are almost identical. Figure 5: _Cont._  
Figure 6 shows the performance of the proposed system and the traditional radio frequency technologies normally used for localization in underground mining in terms of the average localization estimation error. In general, the proposed system completely outperforms other traditional RF technologies. The average localization error for the proposed system is just (10 cm), and 78% of the time the localization error does not exceed (20 cm). That is to say, only 22% of the time the system generates an error of more than (20 cm).