In Fig. 1, there are three coordinate systems, which are the three-dimensional (3-D) world coordinate system, the 3-D camera coordinate system, and the two-dimensional (2-D) image plane coordinate system. Any LED $Pi$ ($i=1,2,\u2026,N$) from the LED array transmitter is imaged into an imaging point $pi$ ($i=1,2,\u2026,N$) in the image plane through the center of the lens. It is assumed that LED $Pi$ ($i=1,2,\u2026,N$) is located at $Pi=(Xi,Yi,Zi)T$ in the 3-D world coordinate system and is known a priori. The imaging point of LED $Pi$ is $pi=(xi,yi)T$ ($i=1,2,\u2026,N$) in the 2-D image plane coordinate system, which can be measured via image processing and signal processing technologies. However, the measurement value of the imaging point is often influenced by noise. When shot noise is the dominant noise source, system noise can be viewed as white Gaussian noise.^{27}^{,}^{28} Hence, our goal is to estimate the location of the camera receiver for white Gaussian noise, to obtain the MLE, and finally derive the CRLB.