## 2 Materials and Methods
### Simulating the Problem Scenarios  
Event data was generated using a combination of ASSET version 1.2 (Air Force Institute of Technology Sensor and Scene Emulation Tool) and v2e version 1.7.0. ASSET is a \"physics-based image-chain model used to generate synthetic electro-optical and infrared (EO/IR) sensor data with realistic radiometric properties, noise characteristics, and sensor artifacts\" [29; 30]. ASSET was specifically chosen for its ability to accurately simulate the frequency dependent impact of the atmosphere on a possible overwhelming constant source. v2e is a Python and OpenCV code that \"generates realistic synthetic DVS event [data] from intensity frames\" at higher resolution [31]. ASSET was used to generate the scene, target, and overwhelming source frame files while v2e transformed those frames into upsampled event data. The primary goal when creating scenes using ASSET and v2e was to simulate event data such that the targets were very challenging to detect through normal visualization techniques. Care was taken to ensure the simulated scenarios were consistent with the operating parameters of hypothetical future real-world system based on existing technology. Different target frequencies and overwhelming source powers were used generate four potential scenarios where the target detection through normal methods ranged from trivial to nearly impossible. Target frequencies were generated in ASSET as a sine wave with power ranging from zero to an apparent signal-to-background radiance of approximately six. The overwhelming source was simulated as a continuous source, using the atmospheric model to generate its temporal characteristics. The frequency of the overwhelming source was approximately 10 Hz with stochastic variations in apparent size on the focal plane array (FPA) due to the atmospheric effects. This overwhelming source frequency is similar to the expected Greenwood frequency at the modeled sensor's high altitude [32]. Each overwhelming source power was chosen to be one order of magnitude greater than the previous. Figure 3 shows the ASSET-simulated target grid without an overwhelming source (left) and the effects of an overwhelming source in the same scene as the targets (right) on a traditional sensor. Both images display the same FOV and viewpoint, demonstrating how much an overwhelming source can affect target detection. Figure 4 shows the ASSET-modeled, normalized apparent radiances of the four overwhelming sources as measured by a traditional sensor, given as the maximum over one FPA dimension, compared to the maximum target apparent radiance normalized to the same scale. These scenarios allow for a range of signal-to-background radiance ratios between approximately 0.0236 and 281, depending on the target location. Figure 5 shows the temporal evolution of the apparent radiance for the strongest overwhelming source along a pixel row passing through its center, as measured by a traditional sensor. The surface plot reiterates the high intensity of the overwhelming source and captures its dynamics, while the color plot indicates the location of the target grid area within those dynamics. Figure 4: ASSET-modeled normalized apparent radiances of the four overwhelming sources as measured by a traditional sensor, given as the maximum over a single FPA dimension. The target’s peak apparent radiance is shown for comparison, normalized to the same scale. Figure 5: Temporal evolution of the apparent radiance for the strongest overwhelming source along a pixel row passing through its center, as measured by a traditional sensor. The surface plot reiterates the high intensity of the overwhelming source and captures its dynamics over time, while the color plot indicates the location of the target grid area within those dynamics. Figure 3: ASSET scene simulation image showing the target grid without an overwhelming source (**left**) and the effects of an overwhelming source in the same scene as the targets (**right**) on a traditional sensor [29; 30]. Both images display the same FOV and viewpoint.