RSOnet: An Image-Processing Framework for a Dual-Purpose Star Tracker as an Opportunistic Space Surveillance Sensor

Self Cite

Space situational awareness (SSA) refers to collecting, analyzing, and keeping track of detailed knowledge of resident space objects (RSOs) in the space environment. With the rapidly increasing number of objects in space, the need for SSA grows as well. Traditional methods rely heavily on imaging RSOs from large, narrow field-of-view (FOV), ground-based telescopes. This research outlines the technology demonstration payload, Resident Space Object Near-space Astrometric Research (RSONAR)—a star tracker-like, wide FOV camera combined with commercial off-the-shelf (COTS) hardware to image RSOs from the stratosphere, overcoming the disadvantages of ground-based observations. The hardware components and software algorithm are described and evaluated. The eligibility of the payload for SSA is proven by the image processing algorithms, which detect the RSOs in the images captured during flight and the survival of the COTS components in the near-space environment. The payload features a low-resolution, wide FOV camera coupled with a Field Programmable Gate Array (FPGA)-based platform that houses the altitude and time-based image capture algorithm. The newly developed payload in a 2U-CubeSat form factor was flown as a space-ready payload on the CSA/CNES stratospheric balloon research platform to carry out algorithm and functionality tests in August 2022.

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stratospheric Night Sky Imaging Payload for Space Situational Awareness (SSA)

Kunalakantha,

Baires,

Dave

et al. 2023

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“…The concept of a dual-purpose star tracker is not new. In [ 4 ], our team demonstrated that STs are cost-effective, flight proven, and require basic image processing to be used as an attitude-determination sensor. An AI-based RSO detection algorithm was presented in this paper “to augment the capabilities of a star tracker by becoming an opportunistic space-surveillance sensor”.…”

Section: Introductionmentioning

confidence: 99%

“…Added to this already challenging task, RSO detection is equally complex and computationally demanding. Most RSO detection relies on AI-based algorithms [ 4 , 14 , 15 ] that are not suitable for real-time operation. Multi-functional, small form-factor STs are not only difficult to develop but require careful planning in mission operation to avoid overloading power, onboard computers, and other spacecraft-level resources.…”

Section: Introductionmentioning

confidence: 99%

A Dual-Purpose Camera for Attitude Determination and Resident Space Object Detection on a Stratospheric Balloon

Chianelli,

Kunalakantha,

Myhre

et al. 2023

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Space systems play an integral role in every facet of our daily lives, including national security, communications, and resource management. Therefore, it is critical to protect our valuable assets in space and build resiliency in the space environment. In recent years, we have developed a novel approach to Space Situational Awareness (SSA), in the form of a low-resolution, Wide Field-of-View (WFOV) camera payload for attitude determination and Resident Space Object (RSO) detection. Detection is the first step in tracking, identification, and characterization of RSOs, including natural and artificial objects orbiting the Earth. A space-based dual-purpose camera that can provide attitude information alongside RSO detection can enhance the current SSA technologies which rely on ground infrastructure. A CubeSat form factor payload with real-time attitude determination and RSO detection algorithms was developed and flown onboard the CSA/CNES stratospheric balloon platform in August 2023. Sub-degree pointing information and multiple RSO detections were demonstrated during operation, with opportunities for improvement discussed. This paper outlines the hardware and software architecture, system design methodology, on-ground testing, and in-flight results of the dual-purpose camera payload.

“…Gyroless star trackers are becoming increasingly important for Space Situational Awareness (SSA) applications [22,23]. Dual-use star trackers are in development to support SSA.…”

Section: Introductionmentioning

confidence: 99%

Treatment of Extended Kalman Filter Implementations for the Gyroless Star Tracker

Critchley-Marrows

Cairns

2022

The literature since Apollo contains exhaustive material on attitude filtering, usually treating the problem of two sensors, a combination of state measuring and inertial devices. More recently, it has become popular for a sole attitude determination device to be considered. This is especially the case for a star tracker given its unbiased stellar measurement and recent improvements in optical sensor performance. The state device indirectly estimates the attitude rate using a known dynamic model. In estimation theory, two main attitude filtering approaches are classified, the additive and the multiplicative. Each refers to the nature of the quaternion update in the filter. In this article, these two techniques are implemented for the case of a sole star tracker, using simulated and real night sky image data. Both sets of results are presented and compared with each other, with a baseline established through a basic linear least square estimate. The state approach is more accurate and precise for measuring angular velocity than using the error-based filter. However, no discernible difference is observed between each technique for determining pointing. These results are important not only for sole device attitude determination systems, but also for space situational awareness object localisation, where attitude and rate estimate accuracy are highly important.