Analysis of satellite laser optical cross sections from the active imaging testbed

Abstract

In a previous paper' the first two authors described two techniques for estimating the optical cross section (OCS) of remotely illuminated objects. This report uses OCS estimates from the Active Imaging Testbed, fielded in 1999 by the Air Force Research Laboratory's Directed Energy Directorate's Surveillance Technologies Branch to analyze the frequency and magnitude of glints. Glints are the transient, non-Lambertian returns from such features as a flat, specular surface or a natural corner cube. The OCS of a sateffite is the least well understood element of the range equation used to estimate system perfonnance. Glints caused by natural corner cubes often exceed the radiometric estimate by orders of magnitudes. However, glints also occur that are on the order of five to ten times the expected returns, due perhaps to the transient alignment of a flat surface. These phenomena can provide increased signal for tracking or imaging applications, but can also act as a noise source. Glints may be identified and their statistics analyzed using the OCS estimation technique. ThITRODUCTIONStrategic systems, such as recent ground-spaceground programs fielded by the US Air Force Research Laboratory (AFRL), employ an esthnate ofthe active optical cross section (OCS) ofthe illuminated object. This assumes the object is a Lambertian reflector with specified reflectivity and size. The OCS is typically the least well characterized element of the range equation. In previous papers, the authors described estimation of system pointing performance based solely on the received time-series si_. In this paper pointing estimates and OCS estimates are used to obtain field estimates of active illumination glints from data that was taken during the Active Imaging Testbed. AfT was fielded in 1999 at the Starfire Optical Range (SOR) on Kirtland AFB, NM, USA. During AlT, 3 1 different satellites were successfully ifiuminated, with more than 100 engagements. Many engagements had several hundred recorded illuminations. These engagements allow for extensive analysis of OCS to provide foundations for future ground-space-ground illumination experiments.Energy requirements for AlT dictated a narrow divergence beam, thus mechanical and atmospheric effects caused frequent offcenter illuminations. Ifan object were illuminated perfectly, a simple inversion ofthe range equation would provide the OCS and detect glints. Two statistical approaches' estimate the OCS from field data. The peak method relies on the fact that while an object may not be filly illuminated, statistically as the number ofshots increases the peak return will approximate that from a flill illumination. The mean method establishes that the average ofmultiple illuminations must statistically represent a fraction of the fill illumination. Both methods provide a statistical distribution of OCS estimates. The key point for the detection of glints is that while the mean approach will not greatly be affected by a return five to ten time larger than expected, the peak method will be greatly sk...

Analytical investigation for the satellite ranging data of changchun-SLR station

“…Some of the parameters such as the power and energy of the laser system, the diameters of the receivers, as well as the effects of the atmosphere are taken into consideration in the range equation. This equation is used to predict the laser system performance (Lukesh et al 2000(Lukesh et al , 2001. Accordingly, the formula of the received energy E recv can be written in the simple form as: Figure 1.…”

Research on space object active detection ladar system imaging simulation

“…While studying the performance of space object active detection ladar system, some researches regard the target satellites as diffuse Lambertian and the kinds of surface materials are the same 5 . Others research the visible light scattering characteristic of space object by using the BRDF method 6 .…”

Modified moment-matching method for estimating pointing parameters in the presence of atmospheric turbulence

“…The chi-square method compares the distribution of the measured signal with the distributions of simulated data, which are created offline using a range of possible boresight and jitter values. The extension of the chi-square method leads to the estimation of the optical cross sections and the shape of the object [7][8][9][10]. Later, Borah et al [3] derived a maximum-likelihood (ML) estimator for measuring boresight and jitter.…”