KEYWORDS: Ranging, Data modeling, Lawrencium, Process modeling, Distance measurement, Pulsed laser operation, Data processing, Laser applications, Laser systems engineering, Lithium
Ranging ability valuation for high-repetition laser ranging system (High-repetition LRS) is essential in space debris measurement. Traditional approaches are usually based on system parameters, such as laser transmission frequency, single pulse energy, transmission aperture, etc. However, precision is not properly evaluated when system conditions varies from ideal conditions. In this paper, a degradation model with a new decrement process based on precision curves is proposed. First, the equation of detection probability and ranging distance is derived. Then, a degradation model to get detection-probability-dependent precision curves is established——a decrement process of data sparsity is simulated, by gradually decreasing effective data while keeping all the noisy data remained. From the curve, a detection probability “threshold” can be seen, from which the ranging ability of the LRS system can be evaluated. In this degradation model, the demanded ranging precision is satisfied automatically. The novel method is reliable and simple with only the detection-probability-dependent precision curve needed. Degradation modeling based on high-repetition ranging experiments for space debris——NORAD 10861, 11574, 16182, 25530 shows an improvement by about 20% in ranging ability evaluation without sacrificing the ranging precision.
Measurement for spin velocity is an important method for identification of space debris from functioning crafts as the
obtained light curve shows periodic signatures, which helps to identify the debris from functioning space craft. In this paper,
space debris of different spin velocities, different altitudes, and different surface materials (Al2O3, TiO2) are both
theoretically analyzed and simulated with a ray tracing method by Tracepro. In the ray tracing simulation, light is presented
by a visible way as light rays, and only some basic laws of geometrical optics are needed. Simulation results show light
curves have periodic signatures which can be used for spin velocity measurement. And spin velocities obtained from active
illumination and passive illumination are different, which may have some reference value in the practical engineering.
Restoration of atmospheric turbulence degraded image is needed to be solved as soon as possible in the field of
astronomical space technology. Owing to the fact that the point spread function of turbulence is unknown, changeable
with time, hard to be described by mathematics models, withal, kinds of noises would be brought during the imaging
processes (such as sensor noise), the image for space target is edge blurred and heavy noised, which making a single
restoration algorithm to reach the requirement of restoration difficult. Focusing the fact that the image for space target
which was fetched during observation by ground-based optical telescopes is heavy noisy turbulence degraded, this paper
discusses the adjustment and reformation of various algorithm structures as well as the selection of various parameters,
after the combination of the nonlinear filter algorithm based on noise spatial characteristics, restoration algorithm of
heavy turbulence degrade image for space target based on regularization, and the statistics theory based EM restoration
algorithm. In order to test the validity of the algorithm, a series of restoration experiments are performed on the heavy
noisy turbulence-degraded images for space target. The experiment results show that the new compound algorithm can
achieve noise restriction and detail preservation simultaneously, which is effective and practical. Withal, the definition
measures and relative definition measures show that the new compound algorithm is better than the traditional
algorithms.
The light curve of space debris can provide the basic target identification information. Photometric data of space target
obtained by ground-based equipment are affected by weather condition, observation equipment, detector performance,
etc. Among these factors, the poor weather condition during the observations could cause worst effects in the
photometric data. The light curves will be smooth and regular under photometric conditions, while irregular in nonphotometric
nights. In addition, we can not distinguish what caused the abnormal brightness variations between weather
and other factors from the traditional photometric data. Our study shows that by obtaining simultaneous light curves of
background stars with an independent telescope close to the main telescope with dedicated observing tactics, we can
verify the influence factors of the photometric variations in non-photometric nights.
Restoration of atmospheric turbulence-degraded image is needed to be solved as soon as possible
in the field of astronomical space technology. This paper discusses the issue of regularization during the
restoration process, a new restoration method of heavy turbulence-degrade image for space target based on
regularization is proposed, in which the anisotropic, nonlinear Step-like and Gussian-like regularization
models are adopted according to the properties of turbulence point spread function(PSF)and image. The
nonlinear regularization functions are suggested to smooth in the process of estimating the PSF and recover
the object image. In order to test the validity of the method, a series of restoration experiments are performed
on the heavy turbulence-degraded images for space target and the experiment results show that the method is
effective to restore the space object from their heavy turbulence-degraded images. Besides, the definition
measures and relative definition measures show that the new method is better than the traditional method for
restoration result.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.