Space Debris Monitoring Research Articles

Method of constructing a space-time grid of variable size images and its application in image processing of landfills

The paper proposes a method of slicing space images into areas of varying sizes to automate the image processing, beginning from the receipt of raw data (download pictures) up to mapping of the underlying surface indices. Indices calculation are based on one image (the surface and the vegetation indices temperature, indices of objects detection on the ground and etc.) and their time series (conducting temporal processing). The downloading of the sources of satellite images algorithm from the sites archives of geodata from the initial data download (the observation area, stage, time period, etc.) is also represented. The procedure of cutting images into segments of varying sizes is described. It allows to use the ?contents? of image both in general and for each pixel of the earth's surface to have a whole time series of the spectral brightness coefficients. Examples of time series of geo-referenced source images and the individual indices of the underlying surface are automatically generated by the algorithm method, for specific problems of space debris monitoring (vegetation indices reaction, the degree of soil degradation, detection of indices).

Evolution of Policies and Technologies for Space Debris Mitigation Based on Bibliometric and Patent Analyses

The lack of technologies for space debris removal and explicit rules for the use of space are jeopardizing the future of space activities. Thus, the objective of this work was to analyse the current scientific research for space debris mitigation, prevention, monitoring and removal. We used bibliometric and patent analyses from the following databases: Space-Track, CelesTrak, Derwent and Web of Science. In this work, the scientific, technological and political actions oriented to space debris mitigation were divided into (1) prevention policies, (2) monitoring and (3) capture. We observed great interest, mainly by the major spacefaring nations, in the development of technologies for detection and removal of space debris from low Earth orbit. This increasing interest to develop feasible technologies and effective policies includes governments, space agencies, universities, institutes and private companies, especially from the main spacefaring nations.

Cache-Related Preemption Delay Analysis for Multilevel Noninclusive Caches

With the rapid growth of complex hardware features, timing analysis has become an increasingly difficult problem. The key to solving this problem lies in the precise and scalable modeling of performance-enhancing processor features (e.g., cache). Moreover, real-time systems are often multitasking and use preemptive scheduling, with fixed or dynamic priority assignment. For such systems, cache related preemption delay (CRPD) may increase the execution time of a task. Therefore, CRPD may affect the overall schedulability analysis. Existing works propose to bound the value of CRPD in a single-level cache. In this article, we propose a CRPD analysis framework that can be used for a two-level, noninclusive cache hierarchy. In addition, our proposed framework is also applicable in the presence of shared caches. We first show that CRPD analysis faces several new challenges in the presence of a multilevel, noninclusive cache hierarchy. Our proposed framework overcomes all such challenges and we can formally prove the correctness of our framework. We have performed experiments with several subject programs, including an unmanned aerial vehicle (UAV) controller and an in-situ space debris monitoring instrument. Our experimental results suggest that we can provide sound and precise CRPD estimates using our framework.

Estimation of the characteristics of a promising orbital lidar for space debris monitoring

A preliminary study aimed at estimating the potential of a promising orbital lidar for space debris monitoring has been performed. Estimates of the space debris detection range under different observation conditions with different technical characteristics of lidar have been calculated. It is shown that the detection range for space debris fragments with sizes of 1 to 10 cm in the wavelength range near 0.5 µm depends strongly on the observation conditions, which are determined by the additive-noise level. It is concluded that a promising orbital lidar should contain a laser emitter with a power of several hundreds of watts and a receiving telescope about 0.5 to 1m in diameter. The possibility of using an orbital lidar for recognizing space debris is estimated. It is shown that a recognition probability exceeding 0.8 can be attained for a space debris image containing several tens of pixels and a signal-to-noise ratio above 10.

The Planned Space Science Utilizations of the New Sardinia 64-m Radio Telescope

This paper describes the technical excellence of the Sardinia Radio Telescope (SRT) design, development status, and the scientific plans foreseen by the Italian Space Agency (ASI) for deep space tracking, radio science, and related scientific opportunities such as near-Earth objects (NEO) and space debris monitoring. SRT, when functioning as a ground tracking station, will eventually provide operational support to spacecraft at four frequencies simultaneously: X-band uplink and downlink as well as Ka-band uplink and downlink. In order to pursue all of its space science objectives, ASI is also considering an agreement with the Italian National Institute for Astrophysics to share a quota of the observing time of the other smaller Italian radio telescopes at Medicina and Noto, where many successful experiments have been conducted with the Ulysses and Cassini missions as well as many other encounters and detections.

Real-time space debris monitoring with EISCAT

Following a feasibility study in 2000–2001 on using the EISCAT ionospheric research radars to detect centimetre-sized space debris in the frame of an ESA contract, we are now finishing a continuation study, aimed at achieving debris detection and parameter estimation in real-time. A requirement is to “piggy-back” space debris measurements on top of EISCAT’s normal ionospheric work, without interfering with that work, and to be able to handle about 500 h of measurements per year. We use a special digital receiver back-end in parallel with EISCAT’s standard receiver. We sample fast enough to correctly band-pass sample the EISCAT analog frequency band. To increase detection sensitivity, we use coherent pulse-to-pulse integration. The coherent integration is built-in in our method of parameter estimation, which we call the match function (MF) method. The method is derived from Bayesian statistical inversion, but reduces, with standard assumptions about noise and prior, to minimizing the least squares norm ∥ z( t) − bχ( R, v, a; t)∥, where z is the measured signal and { bχ} is a set of model signals. Because the model signals depend linearly on the amplitude b, it is sufficient to maximize the magnitude of the inner product (cross correlation) between z and χ, the amplitude estimate is then determined by direct computation. The magnitude of the inner product, when properly normalized, is the MF. To construct the set of model signals, we sample the EISCAT transmission, in the same way as we sample the received signal, and apply linearly changing Doppler-shifts to it. Our initial implementation of the MF-method in 2001 was about four orders of magnitude too slow for real-time applications, but we have now gained the required speed factors. A factor of ten comes from using faster computers, another factor of ten comes from coding our key algorithms in C instead of Matlab. The largest factor, typically 100–300, comes from using a special, approximative, but in practice quite sufficient, method of finding the MF maximum. Test measurements show that we get real-time speed already when using a single dual-processor 2 GHz G5 Macintosh to do the detection computations.