by As spacecraft venture deeper into space, one of the challenges they face is determining their velocity. Without a regular frame of reference, it becomes difficult to gauge how fast they are traveling. While there have been several techniques proposed, one method that has been in development for a significant amount of time is StarNAV, a navigation system that relies solely on the stars.
Various projects named StarNAV are currently underway, including one funded by a NASA Institute for Advanced Concepts grant and a start-up company associated with UC Irvine. In this article, we will focus on the work done by researchers Paul McKee of Rensselaer Polytechnic Institute, Hoang Nguyen and Michael Kudenov of North Carolina State, and John Christian of Georgia Tech. Their research paper, released last year, provides insights into the progress made towards developing a prototype.
The technology behind StarNAV is based on a phenomenon known as stellar aberration, which is defined in the Special Theory of Relativity. Stellar aberration occurs when the velocity of an observer alters the apparent distance between the observer and a star. Although this technique has been used before, previous solutions were plagued by significant errors when calculating a spacecraft’s instantaneous velocity. These solutions typically required a large telescope to measure the inter-star angle in a narrow field of view. By utilizing complex mathematical calculations, it was possible to determine the spacecraft’s velocity from this inter-star angle.
However, obtaining a precise measurement was challenging. To accurately detect the position of a star in an inter-star pair, telescopes with narrow fields of view were required. Consequently, only one star could be tracked per telescope, necessitating a second telescope and a complex tracking system to monitor the alignment of these telescopes. The researchers from NIAC developed a method that relied on slightly less precise inter-star angle measurements but made multiple measurements. By employing sophisticated mathematics, they were able to calculate the spacecraft’s velocity with accuracy, eliminating the need for complicated tracking systems.
The system described in the Acta Astronautica paper involved three telescopes positioned at known angles to each other, with each telescope observing a different pair of stars. By utilizing these three slightly less precise measurements, an algorithm could calculate the average stellar aberration and provide a reasonable estimate of the spacecraft’s velocity.
To validate the accuracy of their system, the authors conducted experiments using a Monte Carlo simulation, a widely accepted test algorithm in mathematics. Though they encountered some confounding factors that would require calibration, the simulation demonstrated that the system could theoretically achieve the same level of accuracy as the best narrow-field-of-view solutions currently available. Additionally, it would be a more cost-effective and user-friendly option.
As a final proof of concept, the researchers created a model to determine the size of the system. They managed to fit it into a 3U CubeSat chassis, measuring approximately 10cm x 30cm x 10cm. Given the modular nature of CubeSat designs, it may be possible to attach this module onto another chassis as part of a comprehensive mission.
While a complete prototype of the system has yet to be built, a similar technology is being commercialized by a start-up, primarily for Earth-based navigation as an alternative to GPS. This technology has garnered interest from military contracts seeking alternate navigation methods in the event that GPS is incapacitated due to enemy action.
As the number of spacecraft embarking on deep space missions increases, there is a growing need to improve their velocity calculation capabilities. StarNAV provides a promising solution, but further development is required to bring it to the prototyping stage.
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1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
Ravina Pandya, Content Writer, has a strong foothold in the market research industry. She specializes in writing well-researched articles from different industries, including food and beverages, information and technology, healthcare, chemical and materials, etc. With an MBA in E-commerce, she has an expertise in SEO-optimized content that resonates with industry professionals.
