A Unified Approach For Optical Survey Strategy Design of Resident Space Objects

Nafi, Akhter Mahmud; Bernard, Arun; Fujimoto, Kohei

doi:10.2514/6.2016-5500

Cited by 1 publication

(1 citation statement)

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“…In early work, [31] information theoretic measures of Fisher Information gain in combination with Lyapunov exponents have been utilized. In recent work, Fujimoto and Nafi [25] investigated different cost function models to evaluated different sensor tasking scenarios, based upon the traditional stripe scanning. Some other strategies are focusing on combining finite set statistics with sensor tasking [5].…”

Section: Introductionmentioning

confidence: 99%

Heuristic and Optimized Sensor Tasking Observation Strategies with Exemplification for Geosynchronous Objects

Frueh

Fielder

Herzog

2018

Journal of Guidance, Control, and Dynamics

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With the new space fence technology, the catalog of known space objects is expected to increase to the order of 100'000 objects. Objects need to be initially detected, and sufficient observations need to be collected to allow for a first orbit determination. Furthermore, the objects have to be re-observed regularly, to keep them in the catalog, as the position uncertainty of the objects increases over time, due to unmodeled dynamic effects. Only a small number of ground-based and even fewer space-based sensors are currently available that are able to collect observations, compared to the large number of objects that need to be observed. This makes efficient sensor tasking, that takes into account the realistic ramifications of the problem, crucial in building up and maintaining a precise and accurate catalog of space objects. The time-varying sensor performance and specific sensor constraints are influenced by the sensor location and observational environmental effects, sensor hardware, processing software and observation modes. This paper shows a new method of solving sensor tasking as an optimization problem translating the heuristic principles that have been successfully applied in sensor tasking of actual SSA networks in a rigorous mathematical framework. A computationally fast near optimal solution is presented, outperforming traditional heuristic sensor tasking methods. Applications of the methodology are shown via the example of the geosynchronous objects listed in the USSTRATCOM two-line element catalog. The results are compared to state of the art observation strategies.

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Section: Introductionmentioning

confidence: 99%