# A Novel Ranging Technique Based on Optical Camera Communications and Time Difference of Arrival
## 2 Brief Literature Review
### Photodiode-Based Visible Light Positioning
The VLP subsystem is very similar to the one presented several years ago by [PERSON] et al. in [28]. The RF subsystem comprises ZigBee-based location hardware. The proposed system requires an offline calibration stage, in which a Convolutional Neural Network is trained using both VLC and RF data. The system exhibits almost perfect accuracy in cell-based location and xy positioning errors around 10 cm for the two tested indoor scenarios. Although the results are interesting, the VLC link samples used during the training phase are obtained with the receiver pointing upwards, which limits the actual usability of the system. Unlike this intrinsic limitation of RSS-based VLP systems, the scheme proposed in this paper is partially immune to misalignment errors. [PERSON] et al. [34] based their work on using the uplink channel impulse response to locate the user. This technique takes advantage of the diffuse components of the uplink channel impulse response for positioning. The authors proposed exploiting the line of sight (LOS) component, the second power peak (SPP) of the impulse response, and the delay time between LOS and SPP for positioning. A proof of concept analysis using fixed reference points with uplink photodetectors is presented. Simulation results show a root mean square (RMS) positioning accuracy of 25 cm and 5 cm for one- and four-detector scenarios, respectively. The effects of multipath propagation in a VLP system based on RSS were studied by [PERSON] et al. [35]. Comparisons with other works where no reflections are considered demonstrate that this phenomenon considerably reduces the positioning accuracy. The authors proposed different calibration approachesto decrease the effect of multipath reflections, such as the strongest signals selection process or the use of dense lamp distributions. [PERSON] et al. studied by simulation the use of very low duty cycle Pulse Positioning Modulation (PPM) in VLP [36]. They aimed to keep VLP and VLC functionalities while maintaining a very low illumination level. They ensured the feasibility of the system, but concluded that higher bandwidth would be needed to process the short light impulse signals. [PERSON] and [PERSON] described a cooperative system for VLP and VLC based on the spread-spectrum plugin of optical identification (OPID) [37]. By keeping the existing IEEE 802.15.7 [38] frame structure untouched, two different implementation schemes were designed by adding the location information field into the communication information field for VLP applications. It is deemed to be an excellent solution to overcome the mutual exclusion between VLP and VLC systems. No implementation or information about expected accuracy is provided. [PERSON] proposed the use of MiniMax filters based on Game Theory instead of Kalman filters in VLP [39], based on the better performance of MiniMax when the statistics of noise sources are not available[PERSON] Results show a better performance of MiniMax when there are disturbances and similar performance of both types when the noise statistics are known. [PERSON] Camera-Based VLP  
As happens in photodiode-based VLP, most contributions are focused on demonstrating the technology. In this case, the systems are based on the transmission of the lamp's Identification (ID) using OCC, and then estimating the position using the geometrical relationships between the captured image and the scenario's geometry. In [40], [PERSON] et al. proposed a VLP system based on image sensors. The system is based on receiving the absolute location information from three LED sources using a camera and estimating the coordinates iteratively as an optimization process. The authors did not comment on how the transmission is carried out, and they reported accuracies in the range of tens of centimeters. [PERSON] et al. presented [41] a VLP system with LED tracking. The authors used a fisheye-lens-equipped camera with 160\({}^{\circ}\) FOV. The LED tracking feature was achieved using optical flow algorithms and the lamp ID transmission was based on a 4-PPM encoding.