Low earth orbit space assets, such as communications satellites, may become the targets of threats in the form of nearby (meters away) satellites. Such threats, due to their often small size, are referred to as micro-sats. Knowledge of the pres-ence of a micro-sat near an asset, in particular its size and relative location, may prove invaluable in determining the danger that the threat presents. Few commercial satellites are launched with the on-board capability to detect the pres-ence of such threats. Complex imaging systems with adaptive optics offer the possibility of threat detection but at prohi-bitive cost for regular use. This paper introduces a non-imaging approach with considerably less expense than adaptive optics based systems. In a previous paper1 the authors presented a novel concept to distinguish between symmetric and oblong objects using a rotating far-field beam pattern. This current paper modifies the approach to consider a far-field pattern that consists of two beams, offset in angle, with one rotating about a stabilized central beam. Creation of the spilt-beams in not difficult optically and rotation may be achieved using a K-mirror. The reflected signal viewed as a time-series, will exhibit a spike when the rotating portion passes over a threat and the angular separation will determine the proximity of the threat to the asset.
Estimating the shape of a target can be an important task in long range surveillance applications. In certain situations
obtaining an adequate spatial image of a target can be problematic, especially when the object size and distance requires
an exceedingly large receiving aperture, or when significant atmospheric turbulence exists between the target and the
receiver. This paper discusses a simple sinusoidal dithering laser illumination scheme that is capable of recovering low
spatial frequency information about the object based on the reflected flux. The approach is analyzed in the presence of
the corrupting influences of beam jitter. The performance of the method is tested through simulations and laboratory
Ground-to-space illumination experiments, such as the Floodbeam I (FBE I, 1993), Floodbeam II (FBE II, 1996) and
Active Imaging Testbed (AIT, 1999), fielded by the Imaging Branch of the United States Air Force Research Laboratory
at Starfire Optical Range (SOR) on Kirtland AFB, NM, obtained considerable information from these highly successful
experiments. While the experiments were primarily aimed at collecting focal/pupil plane data, the authors recognized
during data reduction that the received time-series signals from the integrated full receiver focal plane data contains
considerable hitherto unexploited information.
For more than 10 years the authors have investigated the exploitation of data contained within the time-series signal
from ground-to-space experiments. Results have been presented at numerous SPIE and EOS Remote Sensing Meetings.
In July 2005, the authors were honored as invited speakers at the XIIth Symposium "Atmosphere and Ocean Optics; Atmospheric
Physics" Tomsk, Russia. The authors were invited to return to Tomsk in 2006 however a serious automobile
accident precluded attendance. This paper, requested for publication, provides an important summary of recent results.
Accurate laser beam pointing is critical for a variety of applications including free space laser communications. Several methods have been described in the literature to estimate pointing error parameters. One such estimator is the maximum likelihood estimator that can provide nearly optimal estimates of the pointing error parameters using the signal returned from a target. This paper summarizes the key findings of the maximum likelihood estimator and compares its performance using experimental results.
RHINO, Real-time Histogram Interpretation of Numerical Observations, is a specialty algorithm and tool under development for the United States Air Force Office of Scientific Research (AFOSR). The intent is to provide real-time feedback for adaptive control of telescope pointing for ground-space-ground laser illumination experiments. Nukove together with New Mexico State University first established a proof-of-principle laboratory experiment using RHINO and, under a controlled environment, reduction of the pointing error known as boresight was demonstrated. RHINO is resilient to effects such as glints, speckle, and scintillation. The forthcoming commercially available version of RHINO will use real-time field data and provide adaptive control to the user.
The utility of RHINO is evident in a realistic scenario: Consider a space asset that has been joined by a microsat, perhaps 0.5m in size. The microsat may have been launched to simply listen in from close proximity, monitor the asset, image the asset or most critically, cause damage to the asset. If the goal is to destroy the microsat by long-range illumination with a high power laser and the microsat is meters from the asset (μrads at 1Mm) laser pointing is of utmost importance as the goal is certainly not to damage the space asset. RHINO offers the capability to estimate key metrics of laser system pointing, known as jitter and boresight. The algorithms used have been under development for nearly a decade, have been established in a laboratory environment, and have been tested with field data.
Estimation of a remote object's physical characteristics, such as size, shape and optical cross-section (OCS) can provide valuable strategic and tactical information. Imaging systems, such as those employing adaptive optics, can provide excellent images of space objects through a corrupting atmosphere. However, such systems are extremely expensive when thought of from the viewpoint of queuing sensors. A queuing sensor may interrogate a target of interest on a regular basis and if substantial changes in target characteristics are discovered, the sensor can alert an imaging system to investigate. The techniques discussed in this paper use only the total received time-series signal from a laser illumination experiment. The authors have specialized in the analysis of such signals and have shown that estimates of laser pointing disruptions, known as jitter and boresight, may be made using χ2 tests. Moreover, these estimates, as well as others, may be performed in real time, far more useful than post-processing. Nukove is currently supported by an AFOSR Phase II STTR to develop a prototype software tool to provide realtime estimates and the technique has been demonstrated successfully in a laboratory environment. This paper studies the potential for a well-controlled system to determine approximate target size and shape using statistical χ2 techniques similar to the pointing techniques. Moreover, such estimates may be made in realtime. Since the data is taken from a full aperture and not a focal plane, effects such as speckle and scintillation, which corrupt imaging systems, have been shown to have little impact when the receiving aperture is on the order of one meter or larger.
RHINO, Real-time Histogram Interpretation of Numerical Observations, is a specialty algorithm and tool under development for the United States Air Force Office of Scientific Research. The intent is to provide real-time feedback for adaptive control of telescope pointing for ground-space-ground laser illumination experiments. Nukove together with New Mexico State University first established a proof-of-principle laboratory experiment using RHINO and, under a controlled environment, reduction of the pointing error known as boresight was demonstrated. Additionally, the RHINO algorithm successfully predicted a systematic pointing offset due to solar illumination of a satellite. RHINO is resilient to effects such as glints, speckle, and scintillation. The forthcoming commercially available version of RHINO will use real-time field data and provide adaptive control to the user.
Laser pointing systems suffer from random errors and biases causing off-axis pointing and loss of signal at the target. Often sensors are not available at the target location to provide pointing related information. The present paper outlines a novel technique to adaptively control the beam pointing real-time based on boresight estimates obtained using the statistics of the reflected signal from the target, thus eliminating the need of beam position sensors at the target. A field realization of this technique is discussed. Also a laboratory arrangement that works successfully on this approach is demonstrated.
Automatic target recognition, or target discrimination, is an ever-increasing need in both tactical and strategic engagements. Complex imaging systems, such as those based on adaptive optics compensation, are proven but expensive. This paper addresses a specific problem amenable to non-imaging distinction of targets, specifically symmetric and oblong. The approach is to illuminate a target with a rotating oblong beam, either in the near field (tactical) or far field (strategic). The returns from a symmetric object in the absence of pointing errors will be constant while returns from an oblong object will produce a sinusoidal signal, thus distinguishing the objects without imaging. This paper addresses the result of illumination with an oblong beam, starting with a pure beam, a beam corrupted by atmospheric effects and a beam affected by pointing errors referred to as jitter and boresight.
On September 1, 2003, Nukove Scientific Consulting, together with partner New Mexico State University, began work on a Phase 1 Small Business Technology TRansfer (STTR) grant from the United States Air Force Office of Scientific Research (AFOSR). The purpose of the grant was to show the feasibility of taking Nukove's pointing estimation technique from a post-processing tool for estimation of laser system characteristics to a real-time tool usable in the field. Nukove's techniques for pointing, shape, and OCS estimation do not require an imaging sensor nor a target board, thus estimates may be made very quickly. To prove feasibility, Nukove developed an analysis tool RHINO (Real-time Histogram Interpretation of Numerical Observations) and successfully demonstrated the emulation of real-time, frame-by-frame estimation of laser system characteristics, with data streamed into the tool and the estimates displayed as they are made. The eventual objective will be to use the frame-by-frame estimates to allow for feedback to a fielded system. Closely associated with this, NMSU developed a laboratory testbed to illuminate test objects, collect the received photons, and stream the data into RHINO. The two coupled efforts clearly demonstrate the feasibility of real-time pointing control of a laser system.
When a laser beam propagates through the atmosphere, it is subject to corrupting influences including mechanical vibrations, turbulence and tracker limitations. As a result, pointing errors can occur, causing loss of energy or signal at the target. Nukove Scientific Consulting has developed algorithms to estimate these pointing errors from the statistics of the return photons from the target. To prove the feasibility of this approach for real-time estimation, an analysis tool called RHINO was developed by Nukove. Associated with this effort, New Mexico State University developed a laboratory testbed, the ultimate objective being to test the estimation algorithms under controlled conditions and to stream data into RHINO to prove the feasibility of real-time operation. The present paper outlines the description of this testbed and the results obtained through RHINO when the testbed was used to test the estimation approach.
On September 1, 2003, Nukove Scientific Consulting, together with partner New Mexico State University (NMSU), began work on a Phase I Small Business Technology TRansfer (STTR) grant from the Air Force Office of Scientific Research (AFOSR). The purpose of the grant was to show the feasibility of taking Nukove's pointing estimation technique from a post-processing tool for estimation of laser system characteristics to a real-time tool usable in the field. Nukove's techniques for pointing, shape, and OCS estimation do not require an imaging sensor nor a target board, thus estimates may be made very quickly. To prove feasibility, Nukove developed an analysis tool RHINO (Real-time Histogram Interpretation of Numerical Observations) and successfully demonstrated the emulation of real-time, frame-by-frame estimation of laser system charcteristics, with data streamed into the tool and the estimates displayed as they are made. The eventual objective will be to use the frame-by-frame estimates to allow for feedback to a fielded system. Closely associated with this, NMSU has developed a laboratory testbed to illuminate test objects, collect the received photons, and stream the data into RHINO. The two coupled efforts clearly demonstrate the feasibility of real-time pointing control of a laser system.
In recent papers, the authors have described a non-imaging technique for estimating the shape of remotely illuminated objects. The approach for non-imaging target shape estimation and orientation is model-based. In the absence of pointing errors common to strategic systems, a raster scan by the transmitter would produce the convolution of the expected far-field pattern with the object, providing a starting point for distinguishing targets. The referenced papers show that it is possible to distinguish certain target shapes using a statistical confidence approach based on previous work by the authors. This paper describes a set of shape and orientation χ2 estimation models for several specific targets, pointing jitters and steered boresight angle. Far-field pattern full-widths-at-half maximum comparable to those used in recent field experiments are employed.
Fourier telescopy offers the capability to obtain images of geosynchronous satellites by trading the need for a high power laser and a very large high optical quality receiver for a very large collecting aperture of lower optical quality. The GLINT Program is managed by the US Air Force Research Laboratory and is funded by a congressional add and completion requires continued support. The proposed collector consists of 40 heliostats, each 10m2. The optical quality of the heliostats is not a major issue as the images are obtained by demodulating a received time-series signal. Even with a 4,000m2 collector the energy requirements dictate that as many as 200 pulses must be averaged for each triple product to be obtained. With a laser operating at several Hertz, the collection of data for a single triple product will take minutes and the collection of the full set of triplets for a modest system, will take several hours.
This paper studies strategies for dealing with dynamic solar panels. During an engagement, the body of the satellite will remain fixed relative to the ground site; however the solar panels will turn to point at the sun. Data collected for a full night will be corrupted. One approach is to take data for a short period over many nights at the same solar time. Examples are presented of image quality versus length of time of data collection. The analysis makes uses of the Air Force Research Laboratory’s Time-Domain Analysis and Simulation for Active Tracking (TASAT) code. The amount of time that data may be collected on a given night is compared to the quality of the image recovered. A successful laboratory demonstration of Fourier telescopy is also described.
In a recent paper the authors described a non-imaging technique for estimating the shape of remotely illuminated objects. The approach for non-imaging target shape estimation is model-based. In the absence of up-link energy fluctuations and pointing errors, a raster scan by the transmitter would produce the convolution of the expected far-field pattern with the object, providing a starting point for distinguishing targets. In this setting the referenced paper shows that it is possible to distinguish certain target shapes using a statistical confidence approach based on previous work by the authors. This paper describes a set of target models and a spectrum of far-field pattern full-width-half-maximums (FWHM). Simulations establish the optimal beam size necessary to distinguish among the models using the (chi) 2 statistical confidence. This report addresses the impact of up-link energy fluctuations due to transmitter aperture size DT relative to the Fried coherence length r0. In the regime DT/r0 < 3, the far-field pattern and Strehl fluctuations are well understood. Certain cases, such as small versus large targets, are relatively unaffected by up- link energy fluctuations.
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 satellite is the least well understood element of the range equation used to estimate system performance. 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.
The polarizing characteristics of materials such as paints, metals and dielectrics, are distinct. Measurements of the Stokes vector or the Mueller matrix provide quantitative information about the material characteristics. This paper describes a laboratory experiment, performed under the support of the US Air Force Research Laboratory, the results of which establish the ability to numerically distinguish materials using a non-imaging active laser system. Such an approach is described in the literature as sub-pixel de- mixing.
Laser illumination systems regularly employ an estimation model, referred to as the range equation, to determine system requirements to assure that sufficient signal levels exist. Satellite imaging necessarily employs an estimate of the active optical cross section (OCS) of the illuminated object. This normally assumes the object is a Lambertian reflector. The OCS is typically the least well characterized element of the range equation. In this paper, we use pointing estimates and statistical methods to obtain field estimates of satellite OCS. If an object were illuminated perfectly, a simple inversion of the range equation would provide the OCS. However, for a laser system with a narrow divergence beam, mechanical and atmospheric effects cause frequent off-center illuminations. Because of the random off-center illumination, two statistical approaches, referred to as the peak and mean methods, are described that estimate the OCS and detect non-Lambertian returns known as glints. The peak method relies on the fact that while an object may not be fully illuminated, statistically as the number of shots increases the peak return will approximate that from a full illumination. The mean method establishes that the average of multiple illuminations must statistically represent a fraction of the full illumination. Both methods provide a statistical distribution of OCS estimates and neither requires an imaging system.
Image reconstruction techniques for atmospheric applications often work best with an initial estimate of the object support. This paper examines the ability of a non-imaging laser pointing system to obtain an estimate of target size and shape based on the statistics of the return signal. Fundamental limits on system pointing, such as the tracking errors, corrupt a simple raster scan that would provide gross object shape form the convolution of the far-field pattern with the target. Using techniques developed previously for the estimation of pointing performance, it is possible to distinguish between simple shapes such as bars, circles and T's based on the statistics of the received time signal. Simulated space objects, such as those illuminated during field experiments, may also be distinguished.
Strategic laser system are subject to residual pointing errors arising from such sources as mechanical vibrations, telescope dome turbulence, and atmospheric turbulence. Systems such as those fielded by the Imaging Branch of the Air Force Research Laboratory during the Floodbeam Experiments at Starfire Optical Range, Albuquerque, NM, have energy requirements that dictate that the beam profile at the target must be small. This result in a system where the pointing jitter and boresight represent a sizeable fraction of the beam width. Analysis of result from the first FLoodbeam Experiment suggested a relationship between the simple statistics of the total photon returns and the expected system pointing jitter. Monte Carlo analysis has identified a linear relationship between the simple statistics of total returns and the pointing jitter, and an ideal analytic solution has confirmed the result. The simple relationship requires a substantial number of shots and has a bias in the presence of boresight. A second approach advancing the linear relationship, and based on statistical (chi) 2 techniques, is presented which simultaneously estimates jitter and boresight. Data from both Floodbeam experiments is analyzed. The results are consistent with the consensus view of system pointing performance during the experiments.