Optimization of star research algorithm for esmo star tracker

This paper explains in detail the design and the development of a software research star algorithm, embedded on a star tracker, by the ISAE/SUPAERO team. This research algorithm is inspired by musical techniques. This work will be carried out as part of the ESMO (European Student Moon Orbiter) project by different teams of students and professors from ISAE/SUPAERO (Institut Supe ́rieur de l’Ae ́ronautique et de l’Espace). Till today, the system engineering studies have been completed and the work that will be presented will concern the algorithmic and the embedded software development. The physical architecture of the sensor relies on APS 750 developed by the CIMI laboratory of ISAE/SUPAERO. First, a star research algorithm based on the image acquired in lost-in-space mode (one of the star tracker opera- tional modes) will be presented; it is inspired by techniques of musical recognition with the help of the correlation of digital signature (hash) with those stored in databases. The musical recognition principle is based on finger- printing, i.e. the extraction of points of interest in the studied signal. In the musical context, the signal spectrogram is used to identify these points. Applying this technique in image processing domain requires an equivalent tool to spectrogram. Those points of interest create a hash and are used to efficiently search within the database pre- viously sorted in order to be compared. The main goals of this research algorithm are to minimise the number of steps in the computations in order to deliver information at a higher frequency and to increase the computation robustness against the different possible disturbances

Efficient implementation of the Shack-Hartmann centroid extraction for edge computing

Adaptive optics (AO) is an established technique to measure and compensate for optical aberrations. One of its key components is the wavefront sensor (WFS), which is typically a Shack-Hartmann sensor (SH) capturing an image related to the aberrated wavefront. We propose an efficient implementation of the SH-WFS centroid extraction algorithm, tailored for edge computing. In the edge-computing paradigm, the data are elaborated close to the source (i.e., at the edge) through low-power embedded architectures, in which CPU computing elements are combined with heterogeneous accelerators (e.g., CPUs, field-programmable gate arrays). Since the control loop latency must be minimized to compensate for the wavefront aberration temporal dynamics, we propose an optimized algorithm that takes advantage of the unified CPU/GPU memory of recent low-power embedded architectures. Experimental results show that the centroid extraction latency obtained over spot images up to 700 x 700 pixels wide is smaller than 2 ms. Therefore, our approach meets the temporal requirements of small- to medium-sized AO systems, which are equipped with deformable mirrors having tens of actuators. (C) 2020 Optical Society of Americ

Development of advanced control strategies for Adaptive Optics systems

Atmospheric turbulence is a fast disturbance that requires high control frequency. At the same time, celestial objects are faint sources of light and thus WFSs often work in a low photon count regime. These two conditions require a trade-off between high closed-loop control frequency to improve the disturbance rejection performance, and large WFS exposure time to gather enough photons for the integrated signal to increase the Signal-to-Noise ratio (SNR), making the control a delicate yet fundamental aspect for AO systems. The AO plant and atmospheric turbulence were formalized as state-space linear time-invariant systems. The full AO system model is the ground upon which a model-based control can be designed. A Shack-Hartmann wavefront sensor was used to measure the horizontal atmospheric turbulence. The experimental measurements yielded to the Cn2 atmospheric structure parameter, which is key to describe the turbulence statistics, and the Zernike terms time-series. Experimental validation shows that the centroid extraction algorithm implemented on the Jetson GPU outperforms (i.e. is faster) than the CPU implementation on the same hardware. In fact, due to the construction of the Shack-Hartmann wavefront sensor, the intensity image captured from its camera is partitioned into several sub-images, each related to a point of the incoming wavefront. Such sub-images are independent each-other and can be computed concurrently. The AO model is exploited to automatically design an advanced linear-quadratic Gaussian controller with integral action. Experimental evidence shows that the system augmentation approach outperforms the simple integrator and the integrator filtered with the Kalman predictor, and that it requires less parameters to tune

Hardware Accelerator for Star Centroiding

Since the dawn of civilization mankind has gazed upon the night sky and looked for directions. In this modern age, the stars have proved to be a reliable reference point for navigation in space. From small-satellites for gathering weather data to inter-planetary missions like Cassini Orbiter, figuring out the location of a spacecraft has been done successfully by taking images of star filed visible from the spacecraft, processing and analyzing the image to find the stars and then finding out from a star catalog which part of the sky the patterns of the visible stars best matches. But a lot of calculation is involved in this process which means it takes up huge amount of power and time to complete. In this research work a hardware will be developed that will reduce the power and increase the speed of this process. The accuracy of this design will be tested under different environmental conditions, modeling the actual region of operation of this design which is the space

Autonomous artificial neural netwoek star tracker for spacecraft attitute determination

An artificial neural network based autonomous star tracker prototype for precise spacecraft attitude determination is developed. Night sky testing is used to validate a system consisting of a charged-coupled-device-based camera head unit and integrated control hardware and software. The artificial neural network star pattern match algorithm utilizes a sub catalog of the SKY2000 star catalog. The experimental results are real time comparisons of the star tracker observed motion with the rotational motion of the Earth. The results of a field-programmable-gate-array-based implementation of the star pattern match algorithm are also presented. A new technique of star pattern encoding that removes the star magnitude dependency is presented. The convex hull technique was developed in which the stars in the field of view are treated as a set of points. The convex hull of these points is found and stored as line segments and interior angles moving clockwise from the shortest segment. This technique does not depend on star magnitudes and allows a varying number of stars to be identified and used in calculating the attitude quaternion . This technique combined with feed-forward neural network pattern identification created a robust and fast technique for solving the "lost-in-space" problem. The time required to solve the "lost-in-space" problem for this star tracker prototype is on average 9.5 seconds. This is an improvement over the 60 seconds needed by the current off-the-shelf autonomous star tracker by Ball Aerospace, the CT-633. Initial acquisition after launch as well as recovery from a loss of attitude knowledge during the mission would occur significantly faster with this prototype system when compared to current commercially available autonomous star trackers

Smart cmos image sensor for 3d measurement

3D measurements are concerned with extracting visual information from the geometry of visible surfaces and interpreting the 3D coordinate data thus obtained, to detect or track the position or reconstruct the profile of an object, often in real time. These systems necessitate image sensors with high accuracy of position estimation and high frame rate of data processing for handling large volumes of data. A standard imager cannot address the requirements of fast image acquisition and processing, which are the two figures of merit for 3D measurements. Hence, dedicated VLSI imager architectures are indispensable for designing these high performance sensors. CMOS imaging technology provides potential to integrate image processing algorithms on the focal plane of the device, resulting in smart image sensors, capable of achieving better processing features in handling massive image data. The objective of this thesis is to present a new architecture of smart CMOS image sensor for real time 3D measurement using the sheet-beam projection methods based on active triangulation. Proposing the vision sensor as an ensemble of linear sensor arrays, all working in parallel and processing the entire image in slices, the complexity of the image-processing task shifts from O (N 2 ) to O (N). Inherent also in the design is the high level of parallelism to achieve massive parallel processing at high frame rate, required in 3D computation problems. This work demonstrates a prototype of the smart linear sensor incorporating full testability features to test and debug both at device and system levels. The salient features of this work are the asynchronous position to pulse stream conversion, multiple images binarization, high parallelism and modular architecture resulting in frame rate and sub-pixel resolution suitable for real time 3D measurements

Universal Verification Platform and Star Simulator for Fast Star Tracker Design

Developing star trackers quickly is non-trivial. Achieving reproducible results and comparing different algorithms are also open problems. In this sense, this work proposes the use of synthetic star images (a simulated sky), allied with the standardized structure of the Universal Verification Methodology as the base of a design approach. The aim is to organize the project, speed up the development time by providing a standard verification methodology. Future rework is reduced through two methods: a verification platform that us shared under a free software licence; and the layout of Universal Verification Methodology enforces reusability of code through an object-oriented approach. We propose a black-box structure for the verification platform with standard interfaces, and provide examples showing how this approach can be applied to the development of a star tracker for small satellites, targeting a system-on-a-chip design. The same test benches were applied to both early conceptual software-only implementations, and later optimized software-hardware hybrid systems, in a hardware-in-the-loop configuration. This test bench reuse strategy was interesting also to show the regression test capability of the developed platform. Furthermore, the simulator was used to inject specific noise, in order to evaluate the system under some real-world conditions