IONEA - Instrumento visual de Observação e Navegação para Exploração Autónoma
The main goal of the IONEA project is to develop an integrated set of test & analysis tools, image processing algorithms and an instrument with 3 navigation cameras and a dedicated payload data processor to enable fully autonomous navigation in cislunar & deep space.
Summary
PROJECT DESIGNATION | IONEA – Instrumento Visual de Observação e Navegação para Exploração Autónoma |
|---|---|
PROJECT CODE | POCI-01-0247-FEDER-045192 |
MAIN OBJECTIVE | IONEA aims at developing an integrated toolset (including orbital trajectory design, covariance analysis, test and validation software) as well as navigation cameras and the applicable image processing software to enable automated end-to-end optical navigation for future space missions. |
INTERVENTION REGION | Norte |
BENEFICIARIES ENTITIES | Spin.Works |
APPROVAL DATE | 11-12-2019 |
BEGIN DATE | 01-03-2020 |
CONCLUSION DATE | 28-02-2023 |
TOTAL COST | 626.336,42 EUR |
FINANCIAL SUPPORT FROM EU | FEDER – 395.987,98 EUR |
Activities
- Project Management
- Requirements Analysis
- Mission and Covariance Analysis
- Preliminary Instrument Design
- Detailed Design, Implementation and Integration of the Image Processing Library in FPGA
- Avionics Development
- Detailed Design and Development of the Instrument
- Instrument Assembly, Integration and Laboratory Testing
- Technological Roadmap and Business Development
IONEA Overview
The IONEA activity focuses on the design, development, and testing in a representative environment (TRL5/6) of a space observation and visual navigation instrument, consisting of a high-resolution camera (small angle) and two star sensors, with the objective of enabling fully autonomous navigation for space missions.
In the context of the project, an attempt will be made to remove all fundamental technological obstacles to the construction of a miniaturized product capable of competing in the global space market, a very low-cost visual instrument (below 100k per unit) and that allows autonomous navigation (orientation and positioning) of any type of space vehicle (nano, micro and mini-satellites) in the markets with the greatest potential in the current context of the space sector (Earth observation, interplanetary navigation, and characterization of resources on the Moon and small bodies). The integrated product includes:
- 3 Visual Instruments (a Narrow Angle Camera for precision observation and navigation, and two Star Trackers);
- A High Performance Payload Data Processor;
- Multiple Image Processing algorithms aimed at enabling substantial reduction of observation data prior to download to the ground, as well as continuous extraction of visual navigation data for continuous positioning and guidance anywhere in the inner solar system;
The integrated instrument has been built under strict SWaP (Size, Weight and Power) constraints in order to fit well within a 12-16U Cubesat: (40 x 10 x 10 cm – 4U), 5kg and 20W.
Mission Design
The mission design tasks used in IONEA include the trajectory design of three separate missions:
- An Earth Observation Mission to be performed at a sun-synchronous, 500km Low Earth Orbit
- A Lunar Landing Mission, from launcher separation until landing
- A Small Body Mission, departing from L2 until arrival at the asteroid 65803 Didymos
Once designed, each trajectory was analysed to investigate the navigation accuracy achievable using the previously established requirements for the cameras, on a phase-by-phase basis, in order to guide both the navigation strategy and further adjustments to the pre-determined requirements.
Instrument Development
Two sets of cameras were developed to produce optical navigation measurements:
- a star tracker capable of 3-5 arc-sec attitude estimation (3-sigma), that can also identify planetary and small bodies
- a high-resolution camera capable of about 3.5m/pixel@500km altitude, that can also be used for precision approach and relative navigation in deep space
The star trackers produce attitude estimates throughout the mission and can also help provide lower position estimation accuracies during most phases of a mission. The star trackers can also be used for trajectory refinement when in orbit, or as absolute and relative vision navigation cameras during critical phases such as Deorbit, Descent and Landing (DDL).
On the other hand, and in order to prepare critical manoeuvres, in the vicinity of another body in deep space, and in order to keep high position knowledge whenever needed, the high resolution camera can observe planetary and small bodies against the star background (up to M=10). In cislunar space or in the proximity or another body, the high-resolution camera can also spot surface features to further refine its’ own position.
In addition to the optical intruments, a payload data processor (PDP) based on a COTS architecture (Zynq Ultrascale+) with CPU, GPU and FPGA components as well as an embedded video compression IP core was developed to simultaneously acquire, process, compress, store and forward observations from multiple cameras to extract full 6 DoF (translation and attitude) state estimates during orbital and EDL/DDL missions. This payload data processor is a precursor to an upcoming unit that is currently scheduled to fly in early 2026 in an Earth Observation constellation.
Image Processing
In order to operate the cameras during different mission profiles and produce the type of observables that can be used in the autonomous navigation filter, different image processing algorithms were developed:
- a suitable star tracker algorithm to identify attitude from night sky images
- a feature/object tracking algorithm for target identification and tracking
- a terrain matching algorithm capable of identifying features known a priori in real-time observations, and deriving the camera position
- a time-delay integration (TDI) algorithm to enable significant image enhancement from the overlay of a large set of short exposures
The algorithms were implemented and hardware-accelerated in the payload data processor, enabling real-time image acquisition, processing, compression and storage, including for attitude and translational estimates from images acquired at up to 100Hz.
Laboratory and Field Testing
Each of the developed algorithms were implemented and subsequently tested under realistic conditions in order to prepare for their application in real missions.
Two different setups were deployed to test the algorithms as part of the IONEA project:
- a moving trailer
- a sky observation mount
Dedicated test software tools were developed to operate the cameras under these conditions. Several laboratory and field tests were then conducted in the course of the project in order to calibrate the cameras, test procedures, verify and optimize the test software, obtain realistic image datasets and ultimatly to estimate real-world performance for the camera-algorithm suite.
Follow-up Tests & Applications
In addition to the activities carried out during the execution of IONEA, the Spin.Works team has progressed towards real-world use of the cameras and algorithms as described below:
- The star tracker algorithm was implemented in hardware and tested in preparation of the uPGRADE 6U nanosatellite mission, that Spin.Works expects to launch in the near future;
- The terrain matching algorithm was tested in late 2022 with real images collected with the star tracker along a Mars descent trajectory while on board a drone, as part of the ESA activity AITIVE, having reached TRL5;
- A version of the feature/object tracking algorithm has been implemented for upcoming tests of a terrain-relative navigation (TRN) algorithm as part of ESA’s EL3/Argonaut mission in Q2/2024;
- Finally, a version of the TDI algorithm is currently in space on board the AEROS satellite (launched March 2024).
