Testing Optics and Configuration

 Author: Dr. Michael Zimmer

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According to Ding et al. (2020), Unmanned Aerial Systems (UAS) can support specialized optics and payload while vertically taking off and landing. This support of specialized optics and payload have made UAS usage a preferred mean of intelligence, surveillance, and reconnaissance (ISR). Unmanned Aerial Systems optics and payload are generally assembled onto an aircraft based on mission needs. Embry-Riddle Aeronautical University’s Visual Optics/Thermal Lab allows learners to examine UAS optic and thermal performance while adjusting optic and thermal settings. This paper will explore Embry-Riddle Aeronautical University’s Visual Optics/Thermal Lab from a learner’s perspective while examining payload and sensor capabilities on a single rotary wing UAS platform. Lastly, this paper will discuss on payload and sensor configuration onto an UAS, flight planning, and on a simulated experience in which payload and sensor can be applied into a real-world setting. 

Visual Optics/Thermal Lab

A Visual Optics/Thermal Lab would typically feature optional daylight and FLIR optic capabilities while offering learners to adjust zoom, room temperature, and UAS temperature settings. The daylight option depicts a visual display as the FLIR option allows learners to visualize a man and a single rotary wing UAS under thermal optics. Under default setting, the UAS appears inviable under FLIR. The logic behind the UAS invisibility is because of the labs defaulted room temperature and UAS temperature set at match temperature (73 degrees). Once the room temperature or UAS temperature differs in temperature then heat can be detected. Thermal capabilities hold the advantage over daylight optics in the sense of head tracing which under darken settings a target can be located. Intelligence, Surveillance, and Reconnaissance operators have favored UAS because of such capabilities as thermal imaging (McKenna, 2003). Thermal optics are typically an add-on feature when selecting a particular UAS platform. Unfortunately, not all UAS platforms support thermal as this system tends to increase UAS weight, thus affecting flight performance. Zenmuse is a notable visual sensor system company that provides UAS with daytime (X7), thermal (XT2), and Lidar (L1) options. The X7 allows operators to shot action video at 6K resolution, while the XT2 features a dual-sensor thermal optics, and L1 is noted to offer one of the lightest/highest performing surveying systems in the market.  

UAS Configuration Area/Operation

The Assembly Lab allowed learners configure an UAS and test the UAS configured capabilities in a simulated environment. For this lesson the objective was to study the performance and data capture capabilities of UAS sensors. In addition, the lesson had learners configure a single rotary wing UAS that was equipped with a 4-stoke gas motor (75% fueled), 80w generator, auto-controls (with GPS), infrared senor with gimbal, laser altimeter, single antenna, while using a GCS trailer with a large antenna dish as its station. The simulated real-world environment was set at Yosemite as a central antenna was placed within seven waypoints. The operation was flown under daylight with normal weather conditions. In flight, an animal was identified then used as an example of FLIR capabilities. FLIR allowed for thermal imagining that allowed for the identified animal to become more visible. FLIR capabilities when performing ISR operations aids with the targeting of subjects (Allison et al., 2016). FLIR has been a supportive resource for ISR efforts, yet as technology advances uses in lidar have increased (Krishnan & Saripalli, 2017). Lidar offers a similar passive detection system as FLIR while scanning objects to display 3D images.  

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References

Allison, R., Johnston, J., Craig, G., & Jennings, S. (2016). Airborne optical and thermal remote sensing for wildfire detection and monitoring. Sensors (Basel, Switzerland), 16(8), 1310. https://doi.org/10.3390/s16081310

Ding, J., Mei, H., Lin, C., Zhang, H., & Kiu, W. (2020). Frontier Progress of Unmanned Aerial Vehicles Optical Wireless Technologies. Sensors, 20, 5476. doi:10.3390/s20195476

Krishnan, A. K., & Saripalli, S. (2017). Cross-calibration of RGB and thermal cameras with a LIDAR for RGB-depth-thermal mapping. Unmanned Systems (Singapore), 5(2), 59-78. https://doi.org/10.1142/S2301385017500054

McKenna, T. (2003). Changing of the guard: A variety of ISR tools are useful for maintaining peaceful borders. Journal of Electronic Defense, 26(7), 44.