<p>Cislunar space’s growing importance necessitates robust space domain awareness for its safe and sustainable utilization. Current ground-based surveillance is insufficient to cover the entire Cislunar region of interest, leaving large blind spots. Space-based optical sensors can address this, but due to the vastness of the Cislunar space, sensor placement is challenging. With limited resources, identifying and prioritizing regions of interest for space object custody is crucial. This paper proposes an optimized sensor distribution strategy for Cislunar Space Domain Awareness (CSDA), to maintain custody of objects of interest in the <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40295_2025_522_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$L_2$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>L</mi> <mn>2</mn> </msub> </math></EquationSource> </InlineEquation> Lyapunov and Near Rectilinear Halo Orbits (NRHO), able to perform maneuvers at unknown times. As examples, this work focuses on identifying the key regions spanned by these maneuvering objects in <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40295_2025_522_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$L_2$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>L</mi> <mn>2</mn> </msub> </math></EquationSource> </InlineEquation> Lyapunov and Near Rectilinear Halo Orbits, with maneuver sizes of 0.05 km/s <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40295_2025_522_Article_IEq3.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="25" /> </InlineMediaObject> <EquationSource Format="TEX">$\Delta v$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="normal">Δ</mi> <mi>v</mi> </mrow> </math></EquationSource> </InlineEquation> to 0.5 km/s <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40295_2025_522_Article_IEq3.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="25" /> </InlineMediaObject> <EquationSource Format="TEX">$\Delta v$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="normal">Δ</mi> <mi>v</mi> </mrow> </math></EquationSource> </InlineEquation>. Using dynamical deviation flow in the Circular Restricted Three-Body Problem (CR3BP), critical surveillance regions are identified. The optimal sensor locations are determined by optimizing surveillance coverage for maintained custody using visibility maps.</p>

Cislunar Key Region Surveillance Optimization

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2025年9月24日

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Surabhi Bhadauria,
Arly Black,
Carolin Frueh

摘要

Cislunar space’s growing importance necessitates robust space domain awareness for its safe and sustainable utilization. Current ground-based surveillance is insufficient to cover the entire Cislunar region of interest, leaving large blind spots. Space-based optical sensors can address this, but due to the vastness of the Cislunar space, sensor placement is challenging. With limited resources, identifying and prioritizing regions of interest for space object custody is crucial. This paper proposes an optimized sensor distribution strategy for Cislunar Space Domain Awareness (CSDA), to maintain custody of objects of interest in the $L_2$ $L_{2}$ Lyapunov and Near Rectilinear Halo Orbits (NRHO), able to perform maneuvers at unknown times. As examples, this work focuses on identifying the key regions spanned by these maneuvering objects in $L_2$ $L_{2}$ Lyapunov and Near Rectilinear Halo Orbits, with maneuver sizes of 0.05 km/s $\Delta v$ $Δ v$ to 0.5 km/s $\Delta v$ $Δ v$ . Using dynamical deviation flow in the Circular Restricted Three-Body Problem (CR3BP), critical surveillance regions are identified. The optimal sensor locations are determined by optimizing surveillance coverage for maintained custody using visibility maps.