“Large Scale Radiometric Simulation and Error Assessment of Space-Based Objects,” presented by Tal Bass and Patrick North at the ESA NEO and DEBRIS DETECTION CONFERENCE, 22 – 24 January 2019.
Modeling the performance of remote sensing systems is critical for predicting the detection of targets of interest including near-earth-objects (NEO) and space debris. Earth’s atmosphere has a great impact on ground-based observations, and a target’s material composition, sensor-to-target geometry, and sensor characteristics also affect target detection. High fidelity modeling can therefore be computationally expensive and prohibitive when responding to high-priority time-critical events or processing very large quantities of data or parameters. For this reason, we investigated several modeling approaches of varying fidelity to characterize the performance and error of each.
Each modeling approach simulated the detection of 100 satellites from a ground-based remote sensing facility over the span of a year. The main metrics used to compare the errors associated with each method include:
- Target Intensity
- Irradiance at the Entrance Aperture
- Visual Magnitude
We ran simulations on three separate models: Fast Metrics via STK Engine, Fast Metrics via STK Desktop, and MODerate resolution atmospheric TRANsmission (MODTRAN).
Approximate methods were found to be as much as 1000 times faster than standard evaluation methods, while still agreeing with higher fidelity models if certain preconditions were met.
At the ESA NEO and DEBRIS DETECTION CONFERENCE
poster session in Darmstadt, we will present the performance and errors associated with each radiometric space-based object modeling approach and recommend the best methods of modeling and simulation based on several conditions.
We’re excited to share these next few days with researchers, engineers, and decision makers from all around the world as we talk about the challenges of space situational awareness. There’s no doubt we will learn from and engage with experts on the issue and we look forward to sharing our insights as well.
You can check out the poster here, and feel free to email us if you would like to discuss our findings.