Design and Robust Scheduling of Nano-Satellite
Swarm for Synthetic Aperture Radar Applications
Chee Khiang Pang, Akash Kumar, Cher Hiang Goh, and Cao Vinh Le
Department of Electrical and Computer Engineering
National University of Singapore
Singapore, Singapore 117583
Email: {justinpang, akash, elegch, cvle}@nus.edu.sg
Abstract—This paper presents the design and robust schedul-
ing of nano-satellite (nanosat) swarm for synthetic aperture radar
(SAR) applications. Based on power budget and bandwidth limit
of nanosats, the nanosats’ form factor and swarm size are
chosen to ensure requirements on ground resolution and signal-to-
noise ratio. An energy-efficient and robust scheduling considering
stochastic failures is proposed using scenario optimization with
convexification. The effectiveness of our proposed scheduling
approach is verified with mathematical rigor as well as extensive
simulation results on a realistic SAR application using strip and
spot modes.
I. I NTRODUCTION
With recent advancements in consumer electronics, the
ability to operate co-orbital nano-satellites (nanosats) in swarm
platforms in the same orbit to replace the more costly and
bulkier satellites opens new opportunities and challenges for
space industries [1]. As such, power budget and bandwidth
limit of nanosats must be carefully taken into account when
designing a nanosat swarm. In addition, energy efficiency and
reliability are highly essential scheduling objectives. Due to
restrictive on-board computational capability, given nanosat
specifications and mission details, it is essential for a nanosat
swarm to be properly designed and scheduled prior to launch.
This is opposite to the traditional synthetic aperture radar
(SAR) applications performed by large satellites, where a built-
in scheduler is able to receive the jobs submitted by users and
perform scheduling online [4]–[6].
To the best of our knowledge, design of a nanosat swarm has
only been proposed in [2], considering radar system design and
revisit times for nanosat constellation on different orbits. Dy-
namic scheduling has been recently proposed for cooperative
satellites. In particular, Pemberton and Greenwald identified
the need for dynamic scheduling of imaging satellites in the
presence of uncertain changes in the environment, desired
jobs, as well as the availability of resources [7]. Liao and
Yang formulated a satellite scheduling problem considering
stochastic weather conditions and proposed a solution using a
rolling horizon approach [8]. Wang et al. proposed a heuristic
dispatching rules for dynamic scheduling problem of Earth
observing satellites to deal with uncertain arrival of new
jobs [4]. A satellite mission scheduling problem was studied
This work was supported in part by Singapore MOE AcRF Tier 1 Grant
R-263-000-A52-112.
involving scheduling of jobs to be performed by a satellite in
which new job requests can arrive stochastically [5]. A two-
phase scheduling method is also proposed for the consideration
of emergency jobs in earth observing satellites scheduling [6].
To the best of our knowledge, energy-efficient and robust
scheduling of nanosat swarm considering stochastic failures
has not been considered in state-of-the-art literature. In ad-
dition, the scheduling approaches of existing works were
commonly proposed by a dispatching rule [4] and reschedul-
ing [8][5]. The former has no baseline schedule and jobs are
dispatched online based on a predefined criterion, the latter has
a baseline schedule to be revised multiple times online. These
approaches require online computation and are not suitable for
nanosats.
In this paper, design and robust scheduling of a swarm
of homogeneous nanosats is presented for SAR applications.
Based on power budget and bandwidth limit of nanosats, the
nanosats’ form factor and swarm size are properly chosen
to ensure minimum requirements on ground resolution and
signal-to-noise ratio (SNR). An energy-efficient and robust
scheduling approach considering stochastic failures is then
proposed using convex scenario optimization (CSO). The key
idea of CSO is to find a feasible solution to balance the
energy-optimal schedules from individual scenarios of nanosat
failures, in which occurrence probabilities of scenarios are
formulated using Weibull reliability analysis. Our proposed
CSO is applied to SAR applications in Singapore using strip
and spot modes. The effectiveness of our proposed CSO is ver-
ified with mathematical rigour as well as extensive simulation
results.
II. DESIGN OF NANOSAT SWARM BASED ON POWER
BUDGET AND BANDWIDTH LIMIT
In this section, design of a nanosat swarm for SAR ap-
plications is presented, which includes the following steps:
provision of specifications of nanosats, provision of mission
details, and proposal of nanosats’ form factor and swarm size.
A. Specifications of Nanosats
Nanosats are widely defined as artificial satellites with a wet
mass between 1 and 10 kg (2.2 and 22 lb). The most common
platform to build a nanosat is cubesat, which measures the
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2014 13th International Conference on Control, Automation, Robotics & Vision
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