Event-based cameras bring new perspectives for perception systems by making them faster, smarter, and less energy-consuming. While they are spreading into many application domains, new algorithms are designed to process the data they provide, and new databases are needed to validate and train them. Simulations are an efficient way to increase databases, as they give direct access to ground truth for applications such as target detection or depth estimation, provided the simulation models used are as close as possible to the physical reality. The model should also be designed generically enough to be applicable to different kinds of event-based imagers. The characterization setup proposed in this paper aims at measuring the main characteristics of the dynamic vision sensor in each pixel under outdoor lighting conditions. A simulation model of the imager's response can be generated using the measured characteristics. These measurements are used to estimate the robustness of an algorithm to detect modulated light signals exploiting event-based data. An improvement is then provided so this algorithm can detect higher frequencies.