John R. Henderson

Modeling of adaptive optics-based free-space communications systems

We introduce a wave-optics based simulation code written to model a complete free space laser communications link, including a detailed model of an adaptive optics compensation system. We present the results obtained by this model, where the phase of a communications laser beam is corrected, after it propagates through a turbulent atmosphere. The phase of the received laser beam is measured using a Shack-Hartmann wavefront sensor, and the correction method utilizes a MEMS mirror. Strehl improvement and amount of power coupled to the receiving fiber results for both 1 km horizontal and 28 km slant paths will be presented.

Intelligent sensor tasking for space collision mitigation

Orbital collisions pose a hazard to space operations. Using a high performance computer modeling and simulation environment for space situational awareness, we explore a new paradigm for improving satellite conjunction analysis by obtaining more precise orbital information only for those objects that pose a collision risk greater than a defined threshold to a specific set of satellites during a specified time interval. In particular, we assess the improvement in the quality of the conjunction analysis that can be achieved using a distributed network of ground-based telescopes.

Use of Landsat 5 for Change Detection at 1998 Indian and Pakistani Nuclear Test Sites

An underground nuclear explosion (UNE) can generate a shock wave that lofts surface material, resulting in surface changes that might be detectable. The Comprehensive Nuclear Test-Ban Treaty (CTBT) allows ground and airborne spectral and thermal imaging to help locate such events. Landsat 5 data on the 1998 Indian and Pakistani tests are used here to demonstrate that there are detectable changes in surface features which might be used to localize an underground nuclear test and to develop change detection techniques specific to the use of satellite data to support a CTBT on-site inspection. Landsat 5 has been active for over 20 years providing repeat coverage of the Earths surface every 16 days. Most locations have Landsat data available for a variety of dates, allowing for statistical analysis of the data to understand temporal trends and data variability on a pixel-by-pixel basis. Given the right conditions, these usual patterns of change (such as seasonal changes or weathering) can be discerned from unusual patterns of change, such as features relating to a UNE. This paper extends known change detection techniques to a temporal series of data and shows that multispectral change detection can be used to help localize a UNE.

Image registration and change detection for artifact detection in remote sensing imagery

Image registration is used by the remote sensing community to align images for the purposes of examining changes in a scene. The application in this paper involves finding anomalies associated with human activity for the purpose of detecting underground nuclear explosions. This paper presents a non-rigid image registration algorithm that can be easily implemented using publicly available tools such as python, numpy, scipy, openCV and SIFT. SIFT is used to find feature correspondences between images. An approach based on Mahalanobis distance is used find a subset of robust correspondences. Comparisons are made to the RANSAC algorithm. The imagery was collected by DigitalGlobe’s Worldview-II satellite. One image pair is orthorectified. A second image pair is only geo-registered. Both image pairs were collected over mountainous desert regions, the second image pair has much rougher terrain and presents a challenging situation. The non-rigid property of the image registration algorithm allows for robust registration in mountainous terrain under different viewing geometries. Image differencing of the PAN-chromatic band is used to find changes, some of which are shown in detail for both sets of images. Overall registration improvement is quantified by using the standard deviation of the difference image. The non-rigid warping map was also applied to the multispectral bands of the DigitalGlobe data. This dataset made use of a multivariate change detection algorithm that incorporates the spectral properties of each pixel.

Modeling of Long-Range Atmospheric Lasercom Links Between Static and Mobile Platforms

We describe modeling and simulation of long-range terrestrial laser communications links between static and mobile platforms. Atmospheric turbulence modeling, along with pointing, tracking and acquisition models are combined to provide an overall capability to estimate communications link performance.

Remote measurement of ground source emissivity

The remote measurement of the emissivity of ground materials is of tremendous value in their identification and mapping. Traditional techniques use reflected solar radiation for this measurement for wavelengths shorter than 5 micrometers . With the development of new techniques, the 10 micrometers atmospheric transmission window might also be used for this purpose. Previous work using the multiangle data acquisition technique demonstrated its utility to determine source thermal emission. Here we find the multiangle technique can be used to determine the source specular reflectivity to approximately 0.05 if there is very good system performance.

Multi-angle technique for measurement of ground source emission

TAISIR, the Temperature and Imaging System InfraRed, is a nominally satellite based platform for remote sensing of the earth. One of its design features is to acquire atmospheric data simultaneous with ground data, resulting in minimal dependence on external atmospheric models for data correlation. One technique we employ to acquire atmospheric data is a true multi-angle data acquisition technique. Previous techniques have used only two angles. Here we demonstrate the advantage of using a large number of viewing angles to overconstrain the inversion problem for critical atmospheric and source parameters. For reasonable data acquisition scenarios, simulations show source temperature errors of less than 1 K should be possible. Tradeoffs between flight geometry, number of look angles, and system signal-to- noise are given for typical parameter ranges.

Remote measurement of ground temperature and emissivity

TAISIR, temperature and imaging system infrared, is a nominally satellite based platform for remote sensing of the earth. One of its design features is to acquire atmospheric data simultaneous with ground data, resulting in minimal dependence on external atmospheric models for data correction. Extensive modeling of the rms error of determining a ground temperature and emissivity for a gray body has been performed as a function of integration time, spectroscopic resolution of the system, ground emissivity, atmospheric variables, and atmospheric data accuracy. We find that increased resolution improves measurement accuracy by emphasizing those regions where the atmospheric transmission is highest and atmospheric emission/absorption lowest. We find rms temperature errors <EQ 1 K and rms emissivity errors < 0.01 are obtainable for reasonable seeing and with sufficient information about the atmosphere. A new method is developed for modeling the dependence of the band-averaged transmission and emission. Monte Carlo simulations of satellite data taken using a multi-angle technique are used to derive signal-to-noise requirements. The applicability of those results to the TAISIR system requirements are discussed.