Abstract:
Evaluating overall performance of a ground- and/or space-based SSA "system-of-systems" observational network collecting against thousands of Resident Space Objects (RSO) is very difficult for typical tasking or scheduling-based analysis tools. This is further complicated by networks that have a wide variety of sensor types and phenomena (e.g., optical, radar and passive RF types), each having unique performance, resources, ops tempo, and competing customer and detectability constraints.
We present details of the “Multi-phenomenology Observation Network Evaluation Tool” (MONET), which circumvents these difficulties by assessing the ideal performance of such a network via a digitized supply-vs-demand approach. Cells of each sensor’s supply time are distributed among RSO targets of interest to determine the average performance of the network against that set of RSO targets. Orbit Determination (OD) heuristics are invoked to represent observation quantity and geometry notionally required to obtain the desired orbit estimation quality.
To feed this approach, we derive the detectability and collection rate performance of optical, radar and passive RF sensor physical and performance characteristics. We then prioritize the selected RSO targets according to object size, active/inactive status, orbit regime, and/or other necessary considerations. Finally, the OD-derived tracking demands of each RSO of interest are levied against remaining sensor supply until either (a) all sensor time is exhausted, or (b) the list of RSO targets is exhausted. The outputs from MONET include overall network performance metrics delineated by sensor type and objects and orbits tracked, along with likely orbit accuracies corresponding to the conglomerate network tracking predicted performance.
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Oltrogge, D.L., North, P. and Nicholls, M., “Multi-Phenomenology Observation Network Evaluation Tool (MONET),” AMOS 2014 SSA Conference, Maui HI, 11 September 2014, accessible at https://comspoc.com/Resources/Content/Private/C-20220422T153545/Paper/20140913_Multi-Phenomenology_Observation_Network_Evaluation_Toool_MONET_AMOS_3313692_v22.pdf
