Space Tracking Research Articles

A Loop-Gain-Adaptive-Adjustment Method Based on Fuzzy Logic for Timing Recovery in Space TT&C Systems

This work proposes an loop-gain-adaptive-adjustment (LGAA) algorithm for the timing recovery tracking loop in space tracking, telemetry and command (TT&C) systems. The proposed algorithm generates an adjustment coefficient by using a fuzzy logic (FL) controller, which is designed based on the tracking loop convergence characteristics. The proposed algorithm could enhance the performance of the timing recovery without changing other parameters of the tracking loop. Simulation results show that the proposed LGAA-based tracking loop achieves a better balance between locking time and tracking accuracy compared to the conventional tracking loop that uses a fixed loop gain.

Image convolution techniques integrated with YOLOv3 algorithm in motion object data filtering and detection.

In order to address the challenges of identifying, detecting, and tracking moving objects in video surveillance, this paper emphasizes image-based dynamic entity detection. It delves into the complexities of numerous moving objects, dense targets, and intricate backgrounds. Leveraging the You Only Look Once (YOLOv3) algorithm framework, this paper proposes improvements in image segmentation and data filtering to address these challenges. These enhancements form a novel multi-object detection algorithm based on an improved YOLOv3 framework, specifically designed for video applications. Experimental validation demonstrates the feasibility of this algorithm, with success rates exceeding 60% for videos such as "jogging", "subway", "video 1", and "video 2". Notably, the detection success rates for "jogging" and "video 1" consistently surpass 80%, indicating outstanding detection performance. Although the accuracy slightly decreases for "Bolt" and "Walking2", success rates still hover around 70%. Comparative analysis with other algorithms reveals that this method's tracking accuracy surpasses that of particle filters, Discriminative Scale Space Tracker (DSST), and Scale Adaptive Multiple Features (SAMF) algorithms, with an accuracy of 0.822. This indicates superior overall performance in target tracking. Therefore, the improved YOLOv3-based multi-object detection and tracking algorithm demonstrates robust filtering and detection capabilities in noise-resistant experiments, making it highly suitable for various detection tasks in practical applications. It can address inherent limitations such as missed detections, false positives, and imprecise localization. These improvements significantly enhance the efficiency and accuracy of target detection, providing valuable insights for researchers in the field of object detection, tracking, and recognition in video surveillance.

Robust Artificial Intelligence-Aided Multimodal Rail-Obstacle Detection Method by Rail Track Topology Reconstruction

Detecting obstacles in the rail track area is crucial for ensuring the safe operation of trains. However, this task presents numerous challenges, including the diverse nature of intrusions, and the complexity of the driving environment. This paper presents a multimodal fusion rail-obstacle detection approach by key points processing and rail track topology reconstruction. The core idea is to leverage the rich semantic information provided by images to design algorithms for reconstructing the topological structure of railway tracks. Additionally, it combines the effective geometric information provided by LiDAR to accurately locate the railway tracks in space and to filter out intrusions within the track area. Experimental results demonstrate that our method outperforms other approaches with a longer effective working distance and superior accuracy. Furthermore, our post-processing method exhibits robustness even under extreme weather conditions.

An innovative sCMOS based autonomous astronomical camera dedicated to universal use for SST and other fields of optical astronomy

Creotech Instruments is advancing a game-changing sCMOS camera series. The Final Prototype Model of an astronomical camera for Space Surveillance and Tracking (SST) is in the test campaign phase. Designed for SST, NEO, and debris detection, its adaptable platform suits quantum tech and biological microscopy. Edge computing sets it apart, leveraging FPGA-based SoC for real-time processing and Linux-based pre-processing. Operating autonomously, it supports on-camera ML algorithms, revolutionizing astronomy. Data pre-processing, like frame stacking, reduces data load. This paper introduces the camera's concept, architecture, and prototype test results, emphasizing specific use cases and future product line development.

An orbit determination software suite for Space Surveillance and Tracking applications

The growth of both operational satellites and orbital debris is creating the requirement for more robust Space Surveillance and Tracking (SST)-related applications. These systems necessarily must leverage ground-based sensors (optical and radar) to realise higher performance solutions. In this context, the European Union Space Surveillance and Tracking (EUSST) consortium groups European national agencies and institutions, and is in charge of carrying out the following services: conjunction analysis, fragmentation analysis and re-entry prediction, and the Italian Air Force is in charge of the latter two. In this framework, the Italian SST Operational Centre (ISOC) has recently upgraded its system to the ISOC Suite, an integrated platform providing multiple functions and services in the SST domain. This paper presents the orbit determination functions provided by the novel ISOC Suite. First, a statistical index is computed to assess the measurements correlation to a catalogued object. If it is successful, the object predicted orbit is refined through measurements according either to batch or sequential filters; otherwise these are used to refine a first estimate of the target orbital state computed according to dedicated methodologies. After the presentation of the prototypal software architecture, the ISOC Suite performance are assessed and discussed both in terms of synthetic and real data.

Development of Automatic Assessment Framework for Spine Deformity Using Freehand 3-D Ultrasound Imaging System.

A 3-D ultrasound (US) imaging technique has been studied to facilitate the diagnosis of spinal deformity without radiation. The objective of this article is to propose an assessment framework to automatically estimate spinal deformity in US spine images. The proposed framework comprises four major components, a US spine image generator, a novel transformer-based lightweight spine detector network, an angle evaluator, and a 3-D modeler. The principal component analysis (PCA) and discriminative scale space tracking (DSST) method are first adopted to generate the US spine images. The proposed detector is equipped with a redundancy queries removal (RQR) module and a regularization item to realize accurate and unique detection of spine images. Two clinical datasets, a total of 273 images from adolescents with idiopathic scoliosis, are used for the investigation of the proposed framework. The curvature is estimated by the angle evaluator, and the 3-D mesh model is established by the parametric modeling technique. The accuracy rate (AR) of the proposed detector can be achieved at 99.5%, with a minimal redundancy rate (RR) of 1.5%. The correlations between automatic curve measurements on US spine images from two datasets and manual measurements on radiographs are 0.91 and 0.88, respectively. The mean absolute difference (MAD) and standard deviation (SD) are 2.72° ± 2.14° and 2.91° ± 2.36° , respectively. The results demonstrate the effectiveness of the proposed framework to advance the application of the 3-D US imaging technique in clinical practice for scoliosis mass screening and monitoring.

Multiple correlation filters with gaussian constraint for fast online tracking

The correlation filter based online tracking methods usually can achieve high real-time performance due to the leverage of the well-known FFT. However, they are also apt to generate the “corrupted training samples” in scenarios with complex background, which will trigger the model drift and deteriorate the tracking accuracy rapidly. The existing methods usually consider this problem from certain aspect and none of them has mined the potential of combining multiple formulas. In this paper, we propose the Output Constraint Transfer - Discriminative Scale Space Tracking (OCT-DSST) algorithm, which has taken full consideration of multiple channel feature, multiple filters, kernel trick, memory with incremental learning, and the self-supervision mechanism. We re-formulate the online tracking process by combining all formulas above in a unified framework. The so obtained adaptive learning rate can better exploit the feedback information coming from the intermediate tracking results, and effectively mitigate the corrupted sample problem. The experimental results on the OTB-50/100 and the VOT2016 datasets reveal that the proposed method is comparative to most state-of-the-arts algorithms, and can increase the accuracy by 2% and the success rate by 1.7%, compared to the traditional DSST method.

Adaptive control of BLDC driven robot manipulators in task space

AbstractIn this study, task space tracking control of robot manipulators driven by brushless DC (BLDC) motors is considered. Dynamics of actuators are taken into account and the entire electromechanical system (i.e. kinematic, dynamic, and electrical models) is assumed to include parametric/structured uncertainties. A novel adaptive controller is designed and the stability of the closed loop system is ensured via novel Lyapunov type tools. To demonstrate performance and applicability of the proposed method, a simulation study is conducted using the model of a two degree of freedom, planar robotic manipulator driven by BLDC motors.

In-situ synthesis of spatial heterostructure Ti composites by laser powder bed fusion to overcome the strength and plasticity trade-off

Recent research has focused on laser in-situ additive manufacturing of metal matrix composites with spatially controllable microstructures (phases). This study, inspired by the process of inserting mesh fibers into reinforced concrete, synthesizes TiN in situ using laser powder bed fusion and N2 gas. The laser-melted track, embedded with TiN particles, formed a spatially heterostructured Ti composite (SHTC) with a three-dimensional, artificially controlled architecture in a pure Ti matrix. The influences of process parameters on the mechanical properties of the spatially heterostructured Ti composite and the microstructural evolution of TiN/Ti were investigated emphatically. The results showed that the growth direction of the microstructure was changed by laser powder bed fusion additive manufacturing with alternating N2–Ar gas under suitable N2 concentration and melting track spacing. Among all spatially heterostructured Ti composites, the TiN–Ti heterolayer net-like structure achieved a high ultimate tensile strength of ∼1.0 GPa and elongation of 27 %, demonstrating a superior strength-ductility combination than intrinsic pure Ti and uniform TiN composites, as well as traditional layered structure Ti-based composites. During the tensile test, the deformation behavior was monitored in situ using digital image correlation, and the fracture mechanism was investigated. Hetero-deformation induced strengthening and toughening potentially explains the mechanism behind the strength enhancement of spatially heterostructured Ti composites. Furthermore, this work may stimulate research and development in additive manufacturing of spatial heterostructures with configurable structures, targeting synergistic regulation of strength and ductility in the integration of structure-material-function.

The Channel Fading Influence of the Receiver Operating Characteristics of the TT&C Receiver Based on the Dual-Sequence Frequency Hopping

Aimed at the antijamming needs of the space tracking, telemetry command (TT&C) receiver under a low signal-to-noise ratio, the anti-interference advantage of the dual-sequence frequency hopping (DSFH) communication system is applied. The channel amplitude fading influence of the receiver operating characteristics (ROC) of the TT&C receiver based on the DSFH is studied. Firstly, based on the typical channel model of the Rayleigh fading without direct path transmission, the conditional Fokker-Planck equation (FPE) is obtained by analyzing the statistical independence of the Rayleigh fading signal and SR output particle moments. Secondly, the probability density function (PDF) of the DSFH signal via channel Rayleigh fading enhanced by stochastic resonance (SR) is obtained by introducing the decision time. Thirdly, the detection probability, false alarm probability, ROC, and system bit error rate (BER) of the DSFH signals enhanced by SR under the Rayleigh fading conditions are obtained, under the minimum BER criterion. Finally, the conclusions are reached: one is that the DSFH signals via channel Rayleigh fading can still be detected by the SR system under low SNR, and the other one is that the SNR can reach the -13 dB by the reception of DSFH signal enhanced by SR, when the Rayleigh fading parameter is 0.2042.

Fabrication of polycrystalline diamond micro-milling cutter with different grain sizes by picosecond laser

Polycrystalline diamond (PCD) is an excellent material for machining micro-tools due to its high hardness and wear resistance. However, the diameter of micro-milling tools is generally required to be less than 500 μm. When preparing micro-milling tools with a large aspect ratio, the processing load introduced by traditional grinding methods is easy to cause tool fracture. Therefore, a composite structure of carbide tool holder and diamond tool head is proposed in this paper. A technique of picosecond laser machining PCD micro-milling tool was studied, and the overall manufacturing process of tool blank preparation, nanosecond laser roughing and picosecond laser finishing was formed. A two-dimensional ablation mathematical model for tangential machining of PCD with a multi-pulse picosecond laser was established, and experiments verified the reliability of the mathematical model. In addition, the effects of picosecond laser pulse pitch, pulse energy, and track spacing on the surface quality of PCD materials with different particle sizes and cutting edge radius were studied by orthogonal experiments. The results showed that after picosecond laser processing, the surface roughness (Sa) of PCD with a particle size of 2 μm was the best, which can reach 0.33 μm, and the cutting edge radius of PCD micro-milling tool with a particle size of 25 μm was the smallest, which can get 1.67 μm. Using the optimized picosecond laser parameters, the high-sharpness single-edge micro-milling cutters with different particle sizes PCD with a diameter of 100 μm, aspect ratio greater than 3, and a cutting edge radius less than 3 μm were successfully fabricated.

Improved target detection method for space-based optoelectronic systems

The detection of faint and small targets by space-based surveillance systems is difficult owing to the long distances, low energies, high speeds, high false alarm rates, and low algorithmic efficiencies involved in the process. To improve space object detection and help prevent collisions with critical facilities such as satellites, this study proposes an improved method for the detection of faint and small space-based targets. The proposed method consists of two components: star atlas preprocessing and space-based target detection. The star atlas preprocessing step applies multi-exposure image pyramidal weighted fusion to the original image containing the faint and small space-based target. After obtaining the image pyramidal weighted fusion result atlas, the algorithm employs threshold segmentation to improve the overall image clarity, highlight image details, and provide additional information for target detection. The detection of targets partially relies on the local symmetry of the image. Accordingly, a diffusion function describing the local symmetry is established to precisely locate stars by measuring the symmetry factor in a small area surrounding each pixel in the star atlas. This effectively removes the background stars while retaining high-definition and high-contrast images. The efficacy of the algorithm is validated using simulated datasets consisting of space-based and real images. The results demonstrate that the proposed technique improves the applicability of the multistage hypothesis testing (MHT) method in the context of a complex space environment, thus improving the performance of the space-based electro-optical detection system to better catalogue, identify, and track space targets.

Redirected walking for exploration of unknown environments

Real walking is the most natural locomotion method for exploring Virtual Environments (VE), enhancing the immersion of Virtual Reality (VR). Redirected Walking (RDW) is employed to enable real walking within limited tracking spaces in large VEs by subtly manipulating the mapping between the virtual and real environments. However, the effectiveness of RDW is greatly influenced by the convex shape and size of the manually defined physical tracking space, subsequently impacting the user’s immersive experience. To improve performance, one strategy is to integrate exploration methods from mobile robotics with RDW. This will expand the usable tracking space, facilitating dynamic environments and rapid exploration. For this, we adapted a Unity framework for an RDW algorithm to facilitate simulations for such an exploration. We conducted a simulation with artificially created non-convex explorable tracking spaces and pre-recorded path elements, simulating two adapted RDW artificial potential field (APF) concepts. Three conceptualized modes were applied: repulsive APF, exploration APF, and exploration APF with a distance threshold. Additionally, one APF was extended with a frontier-based exploration approach that utilized the path between the user’s position and a targeted frontier. The analysis revealed a significant trade-off between exploration and immersion. APF combined with frontier-based the exploration technique showed the fastest exploration speed, but - however - resulted in the lowest distance between resets.

A Fast Finite-Time Composite Control With Dynamic Prescribed Performance for Tracking in Task Space of Stewart Parallel Mechanism

A Fast Finite-Time Composite Control With Dynamic Prescribed Performance for Tracking in Task Space of Stewart Parallel Mechanism

Tracking-in-range Formulations for Numerical Optimal Control

In contrast to set-point tracking which aims to reduce the tracking error between the tracker and the reference, tracking-in-range problems only focus on whether the tracker is within a given range around the reference, making it more suitable for the mission specifications of many practical applications. In this work, we present novel optimal control formulations to solve tracking-in-range problems, for problems requiring the tracker to be always in range, as well as problems allowing the tracker to go out of range, which yield overall better outcomes. Since the problem naturally involves discontinuous functions, we present alternative formulations and regularisation strategies to improve the performance of numerical solvers. The extension to in-range tracking with multiple trackers and in-range tracking in high-dimensional space are also discussed and illustrated with numerical examples, demonstrating substantial increases in mission performance in comparison to traditional set-point tracking.

A life cycle assessment study of European Space Agency's space tracking terminal

The transition to a low-carbon and resource-efficient circular economy is a political pillar of the EU and a priority for space agencies.

Disturbance Observer-Based Robust Control for Redundant Manipulators Towards Conditional Monitoring

Conditional monitoring is crucial for preserving the functionality and longevity of electro-mechanical equipment. The adoption of robots is an effective method for improving the traditional approaches that rely on fixed monitoring sites. Therefore, this work investigates the motion control of a redundant robot manipulator in operational space for the application of conditional monitoring. A simple and efficient kinematic tracking differentiator (KTD) is proposed to convert operational space trajectories into joint space tracking. Redundancy is handled using a null space vector with time delay method. Additionally, a fixed-time terminal sliding mode controller (FxTSMC) is designed with a disturbance observer to improve fast convergence and disturbance rejection ability. Simulation results have been demonstrated to show the effectiveness of the proposed control scheme.

Radar observation and recontruction of Cosmos 1408 fragmentation

The population of objects in space has increased dramatically over recent decades. Space debris now represents the majority of objects in space resulting from inactive satellites, breakups, collisions and fragmentations. It has become a concern for institutions all over the world and, as such, it has led to the fostering of several programmes to counter the issues. Among these, the use of ground-based sensors for Space Surveillance Tracking (SST) activities and services and tools for analysing fragmentations play a crucial role.This work presents the activities carried out by Politecnico di Milano, Italian Space Agency and Italian National Institute of Astrophysics in this framework, using data from SST networks and the observation measurements from Bistatic Radar for LEo Survey (BIRALES), an Italian bistatic radar belonging to the EUropean Space Surveillance and Tracking (EUSST), which contributed most to the monitoring of the cloud of fragments. Exploiting Two-Line Elements (TLEs) of observed fragments, a reverse engineering approach is used to reconstruct a fragmentation in orbit through the use of the software suite PUZZLE developed at Politecnico di Milano. The analyses focus on studying the fragmentation of the Cosmos 1408 satellite, which occurred on November 15th 2021 following an Anti-SATellite (ASAT) missile test. More than 1000 trackable pieces and millions of smaller debris (estimated from numerical analysis) were produced by this event, increasing the population of inactive objects around the Earth, and threatening nearby orbiting objects.First, the processing method adopted from BIRALES in observing Cosmos debris is presented and discussed and a critical analysis about the derivable information is conducted. Then, these data and those from SST network observations are used to identify the epoch and the location of the fragmentation. In this procedure, the software toolkit PUZZLE, developed by Politecnico di Milano within a project funded by the Italian Space Agency and extended through the European Research Council, is used.

Future evolutions of EUSST collision avoidance service

Over the last few years, both the space debris population and the number of active satellites in orbit has dramatically increased. The risk of collision for satellite missions is a problem to an increasing extent targeted thoroughly by all agents involved in space situational awareness (SSA) & spacecraft operations. In the frame of the European Union Space Surveillance and Tracking (EU SST), the CA service is provided on a hot redundancy scheme involving the French and Spanish Operations Centres (FR-SSA Centre and S3TOC, respectively), to more than 50 organizations and 390 satellites at the time of writing.Given the dynamic space environment, EU SST CA service must evolve continuously to face the increase of the number of registered users and spacecraft, the diversity of users’ needs and the increasing number of close approaches.

A Novel Registration Method for a Mixed Reality Navigation System Based on a Laser Crosshair Simulator: A Technical Note.

Mixed Reality Navigation (MRN) is pivotal in augmented reality-assisted intelligent neurosurgical interventions. However, existing MRN registration methods face challenges in concurrently achieving low user dependency, high accuracy, and clinical applicability. This study proposes and evaluates a novel registration method based on a laser crosshair simulator, evaluating its feasibility and accuracy. A novel registration method employing a laser crosshair simulator was introduced, designed to replicate the scanner frame's position on the patient. The system autonomously calculates the transformation, mapping coordinates from the tracking space to the reference image space. A mathematical model and workflow for registration were designed, and a Universal Windows Platform (UWP) application was developed on HoloLens-2. Finally, a head phantom was used to measure the system's target registration error (TRE). The proposed method was successfully implemented, obviating the need for user interactions with virtual objects during the registration process. Regarding accuracy, the average deviation was 3.7 ± 1.7 mm. This method shows encouraging results in efficiency and intuitiveness and marks a valuable advancement in low-cost, easy-to-use MRN systems. The potential for enhancing accuracy and adaptability in intervention procedures positions this approach as promising for improving surgical outcomes.