Abstract: Wildfires are becoming increasingly frequent, with potentially
devastating consequences, including loss of life, infrastructure destruction,
and severe environmental damage. Low Earth orbit satellites equipped with
onboard sensors can capture critical information relative to active wildfires
and enable near real-time detection through machine learning algorithms
applied to the acquired data. We propose a framework that automates the
complete wildfire detection and satellite scheduling pipeline, entitled
the WildFire-applicable Intelligent and Responsive Ensemble for Detection
and Scheduling (WildFIRE-DS). This paper develops an algorithm to realize
the vision of the WildFIRE-DS as a proof of concept, integrating three
key components: wildfire detection in satellite imagery, statistical updating
that incorporates data from repeated flyovers, and multi-satellite scheduling
optimization. The algorithm enables wildfire detection using convolutional
neural networks with sensor fusion techniques, incorporates subsequent
flyover information via Bayesian statistics, and schedules a constellation
of satellites using the state-of-the-art Reconfigurable Earth Observation
Satellite Scheduling Problem. Simulated experiments conducted using real-world
wildfire locations and the orbits of operational Earth observation satellites
to demonstrate that this autonomous detection and scheduling approach effectively
enhances wildfire monitoring capabilities.
Abstract: Designing satellite constellation systems involves complex
multidisciplinary optimization in which coverage serves as a primary driver
of overall system cost and performance. Among the various design considerations,
constellation configuration, which dictates how satellites are placed and
distributed in space relative to each other, predominantly determines the
resulting coverage. In constellation configuration design, coverage may
be treated either as an optimization objective or as a constraint, depending
on mission goals. The state-of-the-art literature addresses each mission
scenario on a case-by-case basis, employing distinct assumptions, modeling
techniques, and solution methods. While such problem-specific approaches
yield valuable insights, users often face implementation challenges when
performing tradeoff studies across different mission scenarios, as each
scenario must be handled distinctly. In this paper, we propose a collection
of five mixed-integer linear programs that are of practical significance,
extensible to more complex mission narratives through additional constraints,
and capable of obtaining provably optimal constellation configurations.
The framework can handle various metrics and mission scenarios, such as
percent coverage, average or maximum revisit times, a fixed number of satellites,
spatiotemporally varying coverage requirements, and static or dynamic targets.
The paper presents several case studies and comparative analyses to demonstrate
the versatility of the proposed framework.
@article{WilliamsRogers2025,
author = {{Williams Rogers}, David O. and Won, Dongshik and Koh, Dongwook and Hong, Kyungwoo and Lee, {Hang Woon}},
title = {Optimal Satellite Constellation Configuration Design: A Collection of Mixed Integer Linear Programs},
journal = {Journal of Spacecraft and Rockets},
volume = {0}, number = {0}, pages = {1-18}, year = {0},
doi = {10.2514/1.A36518}
}
Abstract: Because of recent advancements in space technologies, easier
and more economical access to space, and an increase in commercial interests,
the near-Earth space environment has witnessed an exploding number of objects
being put into orbit. In particular, the low Earth orbit (LEO) region is
at an increased risk of orbital collisions from large satellite constellation
projects. Thus, monitoring LEO objects for space domain awareness and space
traffic management has become increasingly imperative. In this paper, we
use the concept of limited-CDF (cumulative distribution function) surface
and mutual information for designing sensor tasking algorithms focusing
on regular observation of known catalog LEO objects (follow-up). Observations
are carried out using simulated ground-based optical telescope(s). The
simulations are representative of realistic observation processes. We investigate
how data from passive space-based sensors can be used to improve the follow-up
performance of the telescope(s). A sensor-tasking framework is developed
in which we conduct a comparative study to assess how different types of
satellite constellation patterns such as Walker-Delta and Walker-Star affect
the overall sensor tasking performance. Through several case studies, we
(1) analyze the appropriate characteristics of the parameters to be optimized
and their impact on the evolution of orbital state uncertainties, (2) compare
different traditional and non-traditional algorithms for sensor tasking
problem, (3) investigate the effect of measurements from different constellation
configurations of passive space-based sensor, and (4) identify a suitable
coordinate system for the limited-CDF surface construction.
@article{Paul2026,
author = {Paul, {Smriti Nandan} and Lee, {Hang Woon}},
title = {Hybrid Sensing for Near-Earth Space Domain Awareness: Leveraging Space-Based Assets for Augmenting Optical Ground Observations},
journal = {The Journal of the Astronautical Sciences},
volume = {73}, number = {1}, year = {2026},
doi = {https://doi.org/10.1007/s40295-025-00546-y}
}
Abstract: Earth observation satellites (EOSs) play a pivotal role in
capturing and analyzing planetary phenomena, ranging from natural disasters
to societal development. The EOS scheduling problem (EOSSP), which optimizes
the schedule of EOSs, is often solved with respect to nadir-directional
EOS systems, thus restricting the observation time of targets and, consequently,
the effectiveness of each EOS. This paper leverages state-of-the-art constellation
reconfigurability to develop the reconfigurable EOS scheduling problem
(REOSSP), wherein EOSs are assumed to be maneuverable, forming a more optimal
constellation configuration at multiple opportunities during a schedule.
This paper develops a novel mixed-integer linear programming formulation
for the REOSSP to optimally solve the scheduling problem for given parameters.
Additionally, since the REOSSP can be computationally expensive for large-scale
problems, a rolling horizon procedure (RHP) solution method is developed.
The performance of the REOSSP is benchmarked against the EOSSP, which serves
as a baseline, through a set of random instances where problem characteristics
are varied and a case study in which Hurricane Sandy is used to demonstrate
realistic performance. These experiments demonstrate the value of constellation
reconfigurability in its application to the EOSSP, yielding solutions that
improve performance, while the RHP enhances computational runtime for large-scale
REOSSP instances.
@article{Pearl2025,
author = {Pearl, Brycen D. and Miller, Joseph M. and Lee, {Hang Woon}},
title = {Reconfigurable Earth Observation Satellite Scheduling Problem},
journal = {Journal of Aerospace Information Systems},
volume = {23}, number = {2}, pages = {136-154}, year = {2026},
doi = {10.2514/1.I011659}
}
Abstract: As orbital debris continues to become a higher priority for
the space industry, there is a need to explore how partnerships between
the public and private space sectors may aid in addressing this issue.
This research develops a space logistics framework for planning orbital
debris remediation missions, providing a quantitative basis for partnerships
that are mutually beneficial between space operators and debris remediators.
By integrating network-based space logistics and game theory, we illuminate
the high-level costs of remediating orbital debris and the surplus that
stands to be shared as a result. These findings indicate significant progress
toward the continued development of a safe, sustainable, and profitable
space economy.
@article{Abdu-Hamid2025,
author = {Abdul-Hamid, Asaad and Pearl, Brycen D. and Lee, {Hang Woon} and Chen, Hao},
title = {Space Logistics Analysis and Incentive Design for Commercialization of Orbital Debris Remediation},
journal = {Journal of Spacecraft and Rockets},
volume = {63}, number = {1}, pages = {218-230}, year = {2026},
doi = {10.2514/1.A36465}
}
Abstract: The significant expansion of the orbital debris population
poses a serious threat to the safety and sustainability of space operations.
This paper investigates orbital debris remediation through a constellation
of collaborative space-based lasers, leveraging the principle of momentum
transfer onto debris via laser ablation. A novel delta-v vector analysis
framework quantifies the cumulative effects of multiple concurrent laser-to-debris
(L2D) engagements by utilizing the vector composition of the imparted delta-v
vectors. The paper formulates the Concurrent Location-Scheduling Optimization
Problem (CLSP) to optimize the placement of laser platforms and the scheduling
of L2D engagements, aiming to maximize debris remediation capacity. Given
the computational intractability of the CLSP, a decomposition strategy
is employed, yielding two sequential subproblems: (1) determining optimal
laser platform locations via the Maximal Covering Location Problem, and
(2) scheduling L2D engagements using a novel integer linear programming
approach to maximize debris remediation capacity. Computational experiments
evaluate the efficacy of the proposed framework across diverse mission
scenarios, demonstrating critical constellation functions such as collaborative
and controlled nudging, deorbiting, and just-in-time collision avoidance.
A sensitivity analysis further explores the impact of varying the number
and distribution of laser platforms on debris remediation capacity, offering
insights into optimizing the performance of space-based laser constellations.
@article{WilliamsRogers2025,
author = {{Williams Rogers}, David O. and Fox, Matthew C. and Stysley, Paul R. and Lee, {Hang Woon}},
title = {Optimal placement and coordinated scheduling of distributed space-based lasers for orbital debris remediation},
journal = {Advances in Space Research},
volume = {76}, number = {9}, pages = {5265-5293}, year = {2025},
doi = {https://doi.org/10.1016/j.asr.2025.07.093}
}
Abstract: This paper proposes an optimization framework for distributed
resource logistics system design to support future multimission space exploration.
The performance and impact of distributed in-situ resource utilization
(ISRU) systems in facilitating space transportation are analyzed. The proposed
framework considers technology trade studies, deployment strategy, facility
location evaluation, and resource logistics after production for distributed
ISRU systems. We develop piecewise linear sizing and cost estimation models
based on economies of scale that can be easily integrated into network-based
mission planning formulations. A case study on a multimission cislunar
logistics campaign is conducted to demonstrate the value of the proposed
method and evaluate key tradeoffs to compare the performance of distributed
ISRU systems with traditional concentrated ISRU. Finally, a comprehensive
sensitivity analysis is performed to assess the proposed system under varying
conditions, comparing concentrated and distributed ISRU systems.
@article{Gkaravela2024,
author = {Gkaravela, Evangelia and Lee, {Hang Woon} and Chen, Hao},
title = {Distributed Space Resource Logistics Architecture Optimization Under Economies of Scale},
journal = {Journal of Spacecraft and Rockets},
volume = {62}, number = {6}, pages = {1654-1666}, year = {2025},
doi = {10.2514/1.A36271}
}
Abstract: Tropical cyclones (TCs) are highly dynamic natural disasters
that travel vast distances and occupy a large spatial scale, leading to
loss of life, economic strife, and destruction of infrastructure. The severe
impact of TCs makes them crucial to monitor such that the collected data
contribute to forecasting their trajectory and severity, as well as the
provision of information to relief agencies. Among the various methods
used to monitor TCs, Earth observation satellites are the most flexible,
allowing for frequent observations with a wide variety of instruments.
Traditionally, satellite scheduling algorithms assume nadir-directional
observations, a limitation that can be alleviated by incorporating satellite
agility and constellation reconfigurability—two state-of-the-art concepts
of operations (CONOPS) that extend the amount of time TCs can be observed
from orbit. This paper conducts a systematic comparative analysis between
both CONOPS to present the performance of each relative to baseline nadir-directional
observations in monitoring TCs. A dataset of 100 historical TCs is used
to provide a benchmark concerning real-world data through maximizing the
number of quality observations. The results of the comparative analysis
indicate that constellation reconfigurability allowing plane-change maneuvers
outperforms satellite agility in the majority of TCs analyzed.
@article{Pearl2023,
author = {Pearl, Brycen D. and Gold, Logan P. and Lee, {Hang Woon}},
title = {Benchmarking Agility and Reconfigurability in Satellite Systems for Tropical Cyclone Monitoring},
journal = {Journal of Spacecraft and Rockets},
volume = {60}, number = {6}, pages = {1811-1824}, year = {2023},
doi = {10.2514/1.A36177}
}
Abstract: The traffic in cislunar space is expected to increase over
the coming years, leading to a higher likelihood of conjunction events
among active satellites, orbital debris, and noncooperative satellites.
This increase necessitates enhanced space domain awareness (SDA) capabilities
that include state estimation for targets of interest. Both Earth surface-based
and space-based observation platforms in geosynchronous orbit or below
face challenges such as range, exclusion, and occlusion that hinder observation.
Motivated by the need to place space-based observers in the cislunar space
regime to overcome these challenges, this paper proposes a cislunar SDA
constellation design and analysis framework that integrates state estimation
into an optimization problem for determining the placement of observers
for optimal state estimation performance on a set of targets. The proposed
multiobserver placement optimization problem samples from a range of possible
target orbits. Upon convergence, the optimized constellation is validated
against a broader set of targets to assess its effectiveness. Two comparative
analyses are presented to evaluate the effects of changes in the sensor
tasking procedure and sensor fidelity on the optimized constellation, comparing
these to a single observer baseline case. The results demonstrate that
the optimized constellations can provide accurate state estimation for
various orbit families.
@article{Clareson2025,
author = {Clareson, Thomas H. and Fox, Matthew C. and Amato, Dominic K. and Lee, {Hang Woon}},
title = {Embedded State Estimation for Optimization of Cislunar Space Domain Awareness Constellation Design},
journal = {Journal of Spacecraft and Rockets},
volume = {62}, number = {3}, pages = {898-914}, year = {2025},
doi = {10.2514/1.A36102}
}
Abstract: This paper addresses the problem of reconfiguring Earth observation
satellite constellation systems through multiple stages. The Multistage
Constellation Reconfiguration Problem (MCRP) aims to maximize the total
observation rewards obtained by covering a set of targets of interest through
the active manipulation of the orbits and relative phasing of constituent
satellites. This paper considers deterministic problem settings in which
the targets of interest are known a priori. We propose a novel integer
linear programming formulation for MCRP, capable of obtaining provably
optimal solutions. To overcome computational intractability due to the
combinatorial explosion in solving large-scale instances, we introduce
two computationally efficient sequential decision-making methods based
on the principles of a myopic policy and a rolling horizon procedure. The
computational experiments demonstrate that the devised sequential decision-making
approaches yield high-quality solutions with improved computational efficiency
over the baseline MCRP. Finally, a case study using Hurricane Harvey data
showcases the advantages of multistage constellation reconfiguration over
single-stage and no-reconfiguration scenarios.
@article{Lee2025,
author = {Lee, {Hang Woon} and Williams Rogers, David O. and Pearl, Brycen D. and Chen, Hao and Ho, Koki},
title = {Deterministic Multistage Constellation Reconfiguration Using Integer Programming and Sequential Decision-Making Methods},
journal = {Journal of Spacecraft and Rockets},
volume = {62}, number = {1}, pages = {206-222}, year = {2025},
doi = {10.2514/1.A35990}
}
Abstract: Cislunar space domain awareness is of increasing interest
to the international community as Earth-Moon traffic is projected to increase,
which raises the problem of placing space-based sensors optimally in a
constellation to satisfy the space domain awareness demand in cislunar
space. This demand profile can vary over space and time, making the design
optimization problem challenging. This paper tackles the problem of satellite
constellation design for spatio-temporally varying coverage demand by leveraging
an integer linear programming formulation. The developed optimization formulation
assumes the circular restricted 3-body dynamics and attempts to minimize
the number of satellites required for the requested demand profile.
@article{Patel2024,
author = {Patel, Malav and Shimane, Yuri and Lee, {Hang Woon} and Ho, Koki},
title = {Cislunar Satellite Constellation Design via Integer Linear Programming},
journal = {The Journal of the Astronautical Sciences},
volume = {71}, number = {3}, pages = {26}, year = {2024},
doi = {10.1007/s40295-024-00445-8}
}
Abstract: A group of satellites, with either homogeneous or heterogeneous
orbital characteristics and/or hardware specifications, can undertake a
reconfiguration process due to variations in operations pertaining to Earth
observation missions. This paper investigates the problem of optimizing
a satellite constellation reconfiguration process against two competing
mission objectives: 1) the maximization of the total coverage reward, and
2) the minimization of the total cost of the transfer. The decision variables
for the reconfiguration process include the design of the new configuration
and the assignment of satellites from one configuration to another. We
present a novel biobjective integer linear programming formulation that
combines constellation design and transfer problems. The formulation lends
itself to the use of generic mixed-integer linear programming (MILP) methods
such as the branch-and-bound algorithm for the computation of provably
optimal solutions; however, these approaches become computationally prohibitive
even for moderately sized instances. In response to this challenge, this
paper proposes a Lagrangian relaxation-based heuristic method that leverages
the assignment problem structure embedded in the problem. The results from
the computational experiments attest to the near-optimality of the Lagrangian
heuristic solutions and a significant improvement in the computational
runtime as compared to a commercial MILP solver.
@article{Lee2023,
author = {Lee, {Hang Woon} and Ho, Koki},
title = {Regional Constellation Reconfiguration Problem: Integer Linear Programming Formulation and Lagrangian Heuristic Method},
journal = {Journal of Spacecraft and Rockets},
volume = {60}, number = {6}, pages = {1828-1845}, year = {2023},
doi = {10.2514/1.A35685}
}
Abstract: The use of regional-coverage satellite constellations is
on the rise, urging the need for an optimal constellation design method
for complex regional coverage. Traditional constellations are often designed
for continuous global coverage, and the few existing regional constellation
design methods lead to suboptimal solutions for periodically time-varying
or spatially varying regional-coverage requirements. This paper introduces
a new general approach to design an optimal constellation pattern that
satisfies such complex regional-coverage requirements. To this end, the
circular convolution nature of the repeating ground-track orbit and common
ground-track constellation is formalized. This formulation enables a scalable
constellation pattern analysis for multiple target areas and with multiple
subconstellations. The formalized circular convolution relationship is
first used to derive a baseline constellation pattern design method with
the conventional assumption of symmetry. Next, a novel method based on
binary integer linear programming is developed, which aims to optimally
design a constellation pattern with the minimum number of satellites. This
binary integer linear programming method is shown to achieve optimal constellation
patterns for general problem settings that the baseline method cannot achieve.
Five illustrative examples are analyzed to demonstrate the value of the
proposed new approach.
@article{Lee2020,
author = {Lee, {Hang Woon} and Shimizu, Seiichi and Yoshikawa, Shoji and Ho, Koki},
title = {Satellite Constellation Pattern Optimization for Complex Regional Coverage},
journal = {Journal of Spacecraft and Rockets},
volume = {57}, number = {6}, pages = {1309-1327}, year = {2020},
doi = {10.2514/1.A34657}
}
Abstract: This paper develops a computationally efficient and scalable
mission planning optimization method for regular space transportation missions,
defined as a set of repeating and periodic interplanetary transportation
missions over a long time horizon after one or a few setup missions. As
more long-term manned missions to Mars are being conceptualized, the need
for a sustainable interplanetary transportation system has become increasingly
prominent. However, planning regular transportation missions with existing
space mission planning optimization formulations has a limitation in computational
scalability in the time dimension. The proposed partially periodic time-expanded
network can address this limitation of the past studies; it is shown to
be computationally scalable and capable of generating solutions that are
practically preferred. Properties of the proposed partially periodic time-expanded
network are analyzed, and a case study reveals that the total initial mass
in the low Earth orbit of regular missions approaches to the theoretical
lower bound as the number of transportation missions increases.
@article{Chen2019,
author = {Chen, Hao and Lee, {Hang Woon} and Ho, Koki},
title = {Space Transportation System and Mission Planning for Regular Interplanetary Missions},
journal = {Journal of Spacecraft and Rockets},
volume = {56}, number = {1}, pages = {12-20}, year = {2019},
doi = {10.2514/1.A34168}
}
Abstract: This paper presents an integrated framework to design a flexible
multi-stage telecommunication satellite configuration deployment strategy
considering the uncertainties in the evolution of the areas of interest
over time. The constructed stochastic demand model considers multiple possible
scenarios for the evolution of the areas of interest with probabilities
based on the market share growth in each area. The optimization aims to
find each stage's design with minimum expected lifecycle cost considering
all possible scenarios. Each stage of the constellation, assumed to be
Flower constellation with circular orbits, provides a regional coverage
of the current area of interest as well as additional coverage for the
potential future areas of interest. The proposed multi-stage satellite
constellation enables the constellation designer to react flexibly and
efficiently to the uncertain future expansion of the areas of interest.
A case study reveals a reduction in the expected lifecycle cost for an
optimized system compared with the all-in-single-stage system and global
coverage constellation.
@article{Lee2018,
author = {Lee, {Hang Woon} and Jakob, Pauline C. and Ho, Koki and Shimizu, Seiichi and Yoshikawa, Shoji},
title = {Optimization of satellite constellation deployment strategy considering uncertain areas of interest},
journal = {Acta Astronautica},
volume = {153}, pages = {213-228}, year = {2018},
doi = {10.1016/j.actaastro.2018.03.054}
}
Conference Papers
Satellite Constellation Design for Tracking Performance in Space Domain Awareness
Dongshik Won,
David Williams Rogers, and
Hang Woon Lee