Review on strategies of space-based optical space situational awareness

Space-based optical(SBO)space surveillance has attracted widespread interest in the last two decades due to its considerable value in space situation awareness(SSA).SBO observation strategy,which is related to the performance of space surveillance,is the top-level design in SSA missions reviewed.The recognized real programs about SBO SAA proposed by the institutions in the U.S.,Canada,Europe,etc.,are summarized firstly,from which an insight of the development trend of SBO SAA can be obtained.According to the aim of the SBO SSA,the missions can be divided into general surveillance and space object tracking.Thus,there are two major categories for SBO SSA strategies.Existing general surveillance strategies for observing low earth orbit(LEO)objects and beyond-LEO objects are summarized and compared in terms of coverage rate,revisit time,visibility period,and image processing.Then,the SBO space object tracking strategies,which has experienced from tracking an object with a single satellite to tracking an object with multiple satellites cooperatively,are also summarized.Finally,this paper looks into the development trend in the future and points out several problems that challenges the SBO SSA.

Jamming Monitoring Technology of the Space Situational Awareness Facilities:A Comprehensive Survey

Complicated electromagnetic environments of the space situational awareness facilities(i.e.,satellite navigation systems,radar)would significantly impact normal operations.Effective monitoring and the corresponding diagnosis of the jamming signals are essential to normal opera-tions and the innovations in anti-jamming equipment.This paper demonstrates a comprehensive survey on jamming monitoring algorithms and applications.The methods in dealing with jamming signals are summarized primarily.Subsequently,the jamming detection,identification,and direc-tion finding techniques are addressed separately.Based on the established studies,we also provide some potential trends of the demonstrated jamming monitoring issues.

Astrometric calibration and source characterisation of the latest generation neuromorphic event-based cameras for space imaging

As an emerging approach to space situational awareness and space imaging,the practical use of an event-based camera(EBC)in space imaging for precise source analysis is still in its infancy.The nature of event-based space imaging and data collection needs to be further explored to develop more effective event-based space imaging systems and advance the capabilities of event-based tracking systems with improved target measurement models.Moreover,for event measurements to be meaningful,a framework must be investigated for EBC calibration to project events from pixel array coordinates in the image plane to coordinates in a target resident space object’s reference frame.In this paper,the traditional techniques of conventional astronomy are reconsidered to properly utilise the EBC for space imaging and space situational awareness.This paper presents the techniques and systems used for calibrating an EBC for reliable and accurate measurement acquisition.These techniques are vital in building event-based space imaging systems capable of real-world space situational awareness tasks.By calibrating sources detected using the EBC,the spatiotemporal characteristics of detected sources or“event sources”can be related to the photometric characteristics of the underlying astrophysical objects.Finally,these characteristics are analysed to establish a foundation for principled processing and observing techniques which appropriately exploit the capabilities of the EBC.

Safe-event pruning in spacecraft conjunction management

Spacecraft conjunction management plays a crucial role in the mitigation of space collisions.When a conjunction event occurs,resources and time are spent analyzing,planning,and potentially maneuvering the spacecraft.This work contributes to a subpart of the problem:Confidently identifying events that will not lead to a high collision probability,and therefore do not require further investigation.The method reduces the dimensionality of the data via principal component analysis(PCA)on a subset of features.High-risk regions are then determined by clustering the projected data,and events that do not belong to a high-risk cluster are pruned.A genetic algorithm(GA)is developed to optimize the number of clusters and feature selection of the model.Furthermore,an ensemble learning framework is proposed to combine the suboptimal models for better generalization.The results show that the first set of parameters pruned approximately 50%of the events in the testing set with no false negatives,whereas the second set of parameters pruned 70%of the events and maintained a near-perfect recall.These results could benefit the optimization of operational resources and allow operators to focus better on the events of interest.

A review of space-object collision probability computation methods

The collision probability computation of space objects plays an important role in space situational awareness,particularly for conjunction assessment and collision avoidance.Early works mainly relied on Monte Carlo simulations to predict collision probabilities.Although such simulations are accurate when a large number of samples are used,these methods are perceived as computationally intensive,which limits their application in practice.To overcome this limitation,many approximation methods have been developed over the past three decades.This paper presents a comprehensive review of existing space-object collision probability computation methods.The advantages and limitations of different methods are analyzed and a systematic comparison is presented.Advice regarding how to select a suitable method for different short-term encounter scenarios is then provided.Additionally,potential future research avenues are discussed.