Photon counting detectors are used in many diverse applications and are well-suited to situations in which a weak signal
is present in a relatively benign background. Examples of successful system applications of photon-counting detectors
include ladar, bio-aerosol detection, communication, and low-light imaging. A variety of practical photon-counting
detectors have been developed employing materials and technologies that cover the waveband from deep ultraviolet
(UV) to the near-infrared. However, until recently, photoemissive detectors (photomultiplier tubes (PMTs) and their
variants) were the only viable technology for photon-counting in the deep UV region of the spectrum. While PMTs
exhibit extremely low dark count rates and large active area, they have other characteristics which make them
unsuitable for certain applications. The characteristics and performance limitations of PMTs that prevent their use in
some applications include bandwidth limitations, high bias voltages, sensitivity to magnetic fields, low quantum
efficiency, large volume and high cost.
Recently, DARPA has initiated a program called Deep UV Avalanche Photodiode (DUVAP) to develop semiconductor
alternatives to PMTs for use in the deep UV. The higher quantum efficiency of Geiger-mode avalanche photodiode
(GM-APD) detectors and the ability to fabricate arrays of individually-addressable detectors will open up new
applications in the deep UV. In this paper, we discuss the system design trades that must be considered in order to
successfully replace low-dark count, large-area PMTs with high-dark count, small-area GM-APD detectors. We also
discuss applications that will be enabled by the successful development of deep UV GM-APD arrays, and we present
preliminary performance data for recently fabricated silicon carbide GM-APD arrays.
This paper describes recent advances in the technology for, and implementation of, short-range non-line-of-sight (NLOS) optical communication links. The approach relies on molecular scattering of ultraviolet wavelengths by the atmosphere to achieve NLOS, omni-directional communication Links. The implementation employs commercially produced semiconductor sources emitting in the solar-blind region of the UV spectrum, around 275nm. This paper extends previously reported field measurements to longer ranges (100+m) and to a wider variety of application scenarios, including an outdoor demonstration of real-time speech at 2.4kbps in full sunlight. The paper also addresses the design trades associated with replacing photomultiplier detectors with semiconductor detectors for reasons of cost and ruggedness. Even with improvements in semiconductor materials and commensurate reduction in dark currents, the use of semiconductor detectors will require the introduction of imaging arrays. Incorporation of imaging arrays opens the possibility of adaptive links in which bandwidth and transmit power are adapted to best exploit the channel constraints.
This paper describes recent advances in the technology for, and implementation of, short-range optical communication links. The approach relies on molecular scattering of ultraviolet wavelengths by the atmosphere to achieve non-line-of-sight, omni-directional communication links. The same technology is also shown to be attractive for certain classes of line-of-sight links. A UV communication testbed implementation is described that is unique, employing research-grade semiconductor sources emitting in the solar-blind region of the UV spectrum, around 275nm.
This paper extends previously reported field measurements to longer ranges and to a wider variety of application scenarios, including operation under tree canopy and operation in short-range quasi-line-of-sight links. Field measurements of atmospheric extinction at 275nm are reported and incorporated in a single-scatter propagation model to predict performance of line-of-sight links. Application of UV communication to foliage penetration uplinks is described, and performance is quantified through field measurements.
Non-line-of-sight (NLOS) ultraviolet (UV) communication appears to be a viable alternative to RF communication for many short-range applications. It exploits both atmospheric scattering and absorption to achieve modest data rates under non line-of-sight (ground-to-ground) and obstructed line-of-sight (foliage penetration) conditions. In this paper, we introduce NLOS optical communication and discuss the advantages of UV over radio (RF) for covert, short-range communication. We then discuss both line-of-sight (LOS) and NLOS measurements performed outdoors in full daylight, and use these measurements to refine a propagation model developed to characterize link performance under various range and background conditions.
Non-line-of-sight ultraviolet (UV) communication technology to support unattended ground sensor communication is described. The concept exploits atmospheric scattering of ultraviolet light to achieve modest data rates under non line-of-sight (ground-to-ground) and obstructed line-of-sight (foliage penetration) conditions. The transmitter consists of a digitally modulated UV source and the receiver employs a sharp cutoff solar-blind absorption filter coupled to a channel photomultiplier module. Prototype semiconductor UV sources with center wavelengths in the solar blind region (<280nm) already offer higher power efficiency than lasers, along with advantages in size, simplicity, and flexibility relative to both lasers and traditional mercury sources. Once commercialized, semiconductor UV sources will also offer significant cost savings over traditional gas-discharge and solid-state UV sources. In this paper, the temporal and spectral properties of a number of prototype semiconductor UV sources are presented and compared to a low-pressure mercury vapor source. Efficient modulation and data coding methods compatible with the output characteristics of both sources are discussed, and measurements from recent test bed experiments are presented.
In battlefield situations, as well as other distributed sensing applications, networks of small, low-cost wireless sensors require short-range communication links that are low-power and difficult to detect at standoff distances (covert). Currently, short-range (< 100m) state-of-the-art ground-to-ground radio frequency (RF) links require line-of-sight for reliable connectivity, and may require 50 to 100 times more power for the transceiver electronics than what is radiated by the transmitter. Furthermore, the RF transmit power necessary to overcome R4 losses near the ground makes the links easily detectable at stand-off ranges unless sophisticated waveforms or highly directive antennas are employed, both of which are inconsistent with low-cost, low-power transceivers. In contrast, baseband optical communication links in the mid-ultraviolet (UV) band can exploit atmospheric scattering to achieve non line-of-sight (NLOS) operation with low-power transceivers at wavelengths that are difficult to detect at stand-off ranges. This paper reviews NLOS UV communication concepts, phenomenology, and the evolution of device technology. A portable communications test bed is described, and recent outdoor tests with 340nm semiconductor emitters are summarized. An indoor FM voice link is described, as an example of the compact form-factor that can be achieved with current technology. The paper concludes with a discussion of potential applications.
A test bed to support research in collaborative sensing by means of energy-constrained, wireless networks is described. The test bed incorporates commercially available sensors and wireless networking technology, with the emphasis on providing a low cost, high-performance, easy to use development environment. The sensors comprising the baseline test bed, acoustic/seismic multimode sensors and panoramic color cameras, are described. A strategy for incorporating new sensors and deploying elements of the test bed to support field tests is described. Results of a field test conducted to demonstrate collaborative tracking, geolocation, and targeting of a tank are summarized. An example of motion detection and image extraction from a panoramic camera is presented.
Time-difference of arrival (TDOA) estimates are an attractive means for geolocation of targets via low-cost, distributed, single-element acoustic sensors. Relative to distributed beamforming approaches. TDOA localization requires significantly less bandwidth between sensor nodes and exhibits greater tolerance to uncertainties in sensor node location and data synchronization. In this paper, we present algorithms for estimating TDOA over low-bandwidth links, and for combining these estimates to provide geolocation of targets. Both of these components are adapted specifically to operation in a low-power, low-bandwidth distributed sensor environment. TDOA estimation is performed using spectral peaks from the acoustic signals, which allows drastic reduction in the bandwidth required to collaboratively determine bearing to target. Previously published localization algorithms were modified to minimize the required communication bandwidth and to support scaling of the algorithm to many distributed nodes. The performance of the various localization algorithms is simulated and compared for several scenarios. The preferred algorithms are also applied to pre-recorded field data and the resulting geolocation estimates are compared to ground truth data.
The constrained energy minimization (CEM) algorithm and the closely related matched filter processor have been widely used for target detection in hyperspectral data exploitation applications. In this paper, we look at the key assumptions underlying the derivation of each algorithm and the effect these assumptions have upon their performance. To illuminate and better understand their operation, we compare both algorithms to Fisher's linear discriminant and the quadratic Bayes classifier. Bayes classifier reduces to Fisher's linear discriminant when the target and background covariances are equal. Furthermore, Fisher's linear discriminant is reduced to the matched filter, when we look for low probability targets. These interrelations can be used to justify the use of the matched filter, which has been developed for the detection of known signals in additive noise, for hyperspectral target which are not corrupted by additive noise. Finally, we investigate under what conditions the output of the matched filter follows a normal distribution.
Atmospheric scattering of ultraviolet light is examined as a mechanism for short-range, non-line-of-sight (NLOS) communication between nodes in energy-constrained distributed sensor networks. A test bed for evaluating NLOS UV communication hardware and modulation schemes is described, and the bit error rate measured in the test bed is used to validate a numerical performance model. Design tradeoffs for a baseband UV transceiver are discussed and performance estimates obtained from the validated numerical model are presented.
The unified treatment of adaptive matched filter algorithms for target detection in hyperspectral imaging data included a theoretical analysis of their performance under a Gaussian noise plus interference model. The purpose of this paper is to provide empirical analysis of algorithm performance using HYDICE data sets. First, we provide a concise summary of adaptive matched filter detectors, including their key theoretical assumptions, design parameters, and computational complexity. The widely used generalized likelihood ratio detectors, adaptive subspace detectors, constrained energy minimization (CEM) and orthogonal subspace projection (OSP) algorithm are the focus of the analysis. Second, we investigate how well the signal models used for the development of detection algorithms characterize the HYDICE data. The accurate modeling of the background is crucial for the development of constant false alarm rate (CFAR) detectors. Finally, we compare the different algorithms with regard to two desirable performance properties: capacity to operate in CFAR mode and target visibility enhancement.
Characterization of the joint (among wavebands) probability density function (PDF) of hyperspectral imaging (HSI) data is crucial for several applications, including the design of constant false alarm rate (CFAR) detectors and statistical classifiers. HSI data are vector (or equivalently multivariate) data in a vector space with dimension equal to the number of spectral bands. As a result, the scalar statistics utilized by many detection and classification algorithms depend upon the joint pdf of the data and the vector-to-scalar mapping defining the specific algorithm. For reasons of analytical tractability, the multivariate Gaussian assumption has dominated the development and evaluation of algorithms for detection and classification in HSI data, although it is widely recognized that it does not always provide an accurate model for the data. The purpose of this paper is to provide a detailed investigation of the joint and marginal distributional properties of HSI data. To this end, we assess how well the multivariate Gaussian pdf describes HSI data using univariate techniques for evaluating marginal normality, and techniques that use unidimensional views (projections) of multivariate data. We show that the class of elliptically contoured distributions, which includes the multivariate normal distribution as a special case, provides a better characterization of the data. Finally, it is demonstrated that the class of univariate stable random variables provides a better model for the heavy-tailed output distribution of the well known matched filter target detection algorithm.
Atmospheric scattering of ultraviolet light is examined as a mechanism for short-range, non-line-of-sight (NLOS) communication between nodes in energy-constrained distributed sensor networks. The physics of scattering is discussed and modeled, and progress in the development of solid state sources and detectors is briefly summarized. The performance of a representative NLOS UV communication system is analyzed by means of a simulation model and compared to conventional RF systems in terms of covertness and transceiver power. A test bed for evaluating NLOS UV communication hardware and modulation schemes is described.
In this paper, we introduce a set of taxonomies that hierarchically organize and specify algorithms associated with hyperspectral unmixing. Our motivation is to collectively organize and relate algorithms in order to assess the current state-of-the-art in the field and to facilitate objective comparisons between methods. The hyperspectral sensing community is populated by investigators with disparate scientific backgrounds and, speaking in their respective languages, efforts in spectral unmixing developed within disparate communities have inevitably led to duplication. We hope our analysis removes this ambiguity and redundancy by using a standard vocabulary, and that the presentation we provide clearly summarizes what has and has not been done. As we shall see, the framework for the taxonomies derives its organization from the fundamental, philosophical assumptions imposed on the problem, rather than the common calculations they perform, or the similar outputs they might yield.
Real-time detection and identification of military and civilian targets from airborne platforms using hyperspectral sensors is of great interest. Relative to multispectral sensing, hyperspectral sensing can increase the detectability of pixel and subpixel size targets by exploiting finer detail in the spectral signatures of targets and natural backgrounds. A multitude of adaptive detection algorithms for resolved or subpixel targets, with known or unknown spectral characterization, in a background with known or unknown statistics, theoretically justified or ad hoc, with low or high computational complexity, have appeared in the literature or have found their way into software packages and end-user systems. The purpose of this paper is threefold. First, we present a unified mathematical treatment of most adaptive matched filter detectors using common notation, and we state clearly the underlying theoretical assumptions. Whenever possible, we express existing ad hoc algorithms as computationally simpler versions of optimal methods. Second, we assess the computational complexity of the various algorithms. Finally, we present a comparative performance analysis of the basic algorithms using theoretically obtained performance characteristics. We focus on algorithms characterized by theoretically desirable properties, practically desired features, or implementation simplicity. Sufficient detail is provided for others to verify and expand this evaluation and framework. A primary goal is to identify best-of-class algorithms for detailed performance evaluation.
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