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We present here a new PSF-shaping technique using biaxial crystals to generate a highly z-dependent distribution in single molecule localization microscopy (SMLM). This distribution features two zeros of intensity that rotate together with defocus. This PSF features similarities to the double-helix introduced by Moerner and Piestun and thus has been dubbed dark-helix since we track zeros of intensity. Preliminary numerical studies based on Cramer-Rao Lower Bound (CRLB) show that this PSF has the potential to obtain up to 20nm localization precision. This PSF can be easily generated by a very simple, monolithic add-on added in front of the detection camera. Additionally, the PSF remains of the approximate size of the Airy PSF, the x-y localization precision is not substantially affected and no trade-off is required. The xy compacity of the PSF also enables theoretically a higher density of emitters than the double-helix which spreads on a larger scale. Limiting factors for SMLM such as loss of photons, complexity and robustness will be discussed and considerations about the practical implementation of such techniques will be given.

Purpose: In-Depth photon counting detectors (PCXD) use an edge-on configuration and have multi-layer segmentations. The benefit of this configuration for additional spectral information depends on the energy response. Also, inter-layer cross-talk introduces correlation to the signal collected from each layer, which makes the independent Poisson model no longer valid for estimating the Cramer-Rao lower bound (CRLB) of the material decomposition variance. We proposed to use a multivariate Gaussian model as the substitute address the data correlation. Methods: A 120 kVp incident spectrum was simulated and transmitted through 25cm of water and 1cm of calcium. 5- layer In-Depth and 1-layer Edge-On PCXDs with full energy resolution were simulated using Monte Carlo methods. We selected Si, GaAs and CdTe as detector materials. The detectors were defined to have 1mm wide pixels and thickness of 70mm (Si), 10.5mm (GaAs) and 3mm (CdTe). Geant4 was used and energy response functions (ERF) capturing secondary events were obtained, together with the Gaussian parameter estimates. We evaluated the CRLBs of the In-Depth and Edge-On detectors for each material and the systematic variance bounds were compared. Results: For uncorrelated data, the CRLB can assume Poisson statistics. As the data becomes more correlated, the Poisson CRLB fails to capture the cross-talk effect, but a Gaussian model can, and is accurate if the number of photons is not small. The CRLB analysis shows that the effects of the ERF and the noise correlation are significant. If cross-talk can be corrected, the depth information proves to be beneficial and can reduce the variance lower bound by 3% to 10% depending on the detector material. Conclusions: The multivariate Gaussian model was validated to be a good substitute to the Poisson model for PCXD CRLB estimation. It can avoid the errors that would otherwise be caused by correlated measurements.

Energy-discriminating, photon counting (EDPC) detectors have been proposed for CT systems for their spectral imaging capabilities, improved dose efficiency and higher spatial resolution. However, these advantages disappear at high flux because of the damaging effects of pulse pileup. From an information theoretic standpoint, spectral information is lost. The information loss is particularly high when we assume that the EDPC detector extracts information using a bank of comparators, as current EDPC detectors do. We analyze the use of alternative pulse detection logic which could preserve information in the presence of pileup. For example, the peak-only detector counts only a single event at the peak energy of multiple pulses which are piled up. We describe and evaluate five of these alternatives in simulation by numerically estimating the Cramer-Rao lower bound of the variance. At high flux, alternative mechanisms outperform comparators. In spectral imaging tasks, the variance reduction can be as high as an order of magnitude.

During model-based image dehazing, the role of the accuracy of transmission estimation is crucial, which has a decisive effect on the final result. Considering that an ideal transmission map must be smooth, edge-preserving and free of redundant false details, a fusion-based dark channel prior (DCP) dehazing algorithm is presented in this paper. On the basis of DCP, a pixel-wise and a patch-wise transmission maps are obtained. Then an L0 smoothing filter and a large scale Gaussian filter are applied to them respectively. Finally, a much more accurate refined transmission map is attained through fusion and a haze-free image is restored using the atmosphere degradation model. Furthermore, a novel scheme for setting the lower bound of transmission adaptively is also put forward. Experiments demonstrate a better and faster dehazing capability over original DCP algorithm and state-of-the-art dehazing methods, especially in suppressing halo artifacts, restoring details and coping with the haze existing in small-scale areas of depth discontinuity occluded by foreground..

The phase diversity wavefront sensing (PDWFS) technique is an a posteriori image-based wavefront sensing technique which has been successfully implemented to the Hubble Space Telescope. The analytical form for the phase diversity Cramer-Rao lower bound(CRLB) of Golay3 aperture is firstly derived. Monte Carlo analysis of the PDWFS CRLB is used due to the dependence of CRLB on the true values of aberration parameters being estimated. Then the ensemble average of mean-squared errors(MSE) quantities of CRLB is used to evaluate the performance of imaging schemes with different photon distributions and different amounts of defocus. The numerical simulation shows that for a point source target, if a third image implies the inclusion of extra photons, the MSE would be reduced to a degree in accordance with the amount of the extra photons, the MSE remains nearly unchanged if the totoal photons is finite, no matter for a two-channel or a three-channel system. We also find that varying the defocus of one image becomes meaningless if the defocus of the other image is at a high level.

We consider light trapping in photonic crystals in the weak material absorption limit. Using a rigorous electromagnetic approach, we show that the upper bound on the angle-integrated absorption enhancement by light trapping is proportional to the photonic density of states. The tight bound can be reached if all the states supported by the structure are coupled to external radiation. Numerical simulations are used to illustrate the theory and the design of both two- and three-dimensional photonic crystals for the purpose of light trapping. Using the van Hove singularities, the angle-integrated absorption enhancement in two-dimensional photonic crystals could surpass the conventional limit over substantial bandwidths.

In this paper we introduce Spatially Aware Expectation Maximization (SpAEM), a new parameter estimation method which incorporates information pertaining to spatial prior probability into the traditional expectation- maximization framework. For estimating the parameters of a given class, the spatial prior probability allows us to weight the contribution of any pixel based on the probability of that pixel belonging to the class of interest. In this paper we evaluate SpAEM for the problem of prostate capsule segmentation in transrectal ultrasound (TRUS) images. In cohort of 6 patients, SpAEM qualitatively and quantitatively outperforms traditional EM in distinguishing the foreground (prostate) from background (non-prostate) regions by around 45% in terms of the Sorensen Dice overlap measure, when compared against expert annotations. The variance of the estimated parameters measured via Cramer-Rao Lower Bound suggests that SpAEM yields unbiased estimates. Finally, on a synthetic TRUS image, the Cramer-Von Mises (CVM) criteria shows that SpAEM improves the estimation accuracy by around 51% and 88% for prostate and background, respectively, as compared to traditional EM.

Unlike conventional x-ray absorption imaging, x-ray differential phase contrast imaging (DPCI) uses a phase retrieval algorithm to obtain x-ray phase information from a group of x-ray intensity measurements. As a result, the noise performance of DPCI is expected to differ from that of x-ray absorption imaging. Given the total number of x-ray photons used in imaging, lower noise variance in estimated phase contrast images suggests superior dose efficiency, which is one of the most desirable feature in x-ray imaging. When an algorithm is used to retrieve the phase information, it is important to understand what the lowest possible noise variance would be and whether the algorithm used to retrieve the phase information yields the lowest possible noise variance. To address these questions for differential phase contrast imaging, we studied the noise performance of DPC imaging using the powerful Cramer-Rao lower bound (CRLB) in statistical signal estimation method. Results demonstrated that the noise variances in DPCI images obtained by the algorithmic phase retrieval are always higher than the CRLB, which implies a possible sub-optimality of current phase estimation method. The results also call for the need to apply statistical signal estimation theory to DPCI in order to further improve its noise performance and dose efficiency.

Target location is a fundamental application in aerial image process. In this work, a fast normalized cross correlation algorithm is proposed for the application of target location in aerial image. Firstly, normalized cross correlation has been proved equivalent to Euclidean distance. In the search step, the target template and the corresponding window of base image are projected to a set of mutually orthonormal vectors for calculating the lower bound of the distance, where the windows with too large distance relative to the target template will be rejected in this step. Finally, the directly normalized cross correlation calculating is applied to the rest windows of base image to achieve the final correct location of target. The experimental results show that compared with traditional method, the proposed method significantly improved the computational complexity without sacrificing the spatial resolution or the accuracy of the match result.

Cooperative communication has been recently proposed in wireless communication systems for exploring the inherent spatial diversity in relay channels.The Amplify-and-Forward (AF) cooperation protocols with multiple relays have not been sufficiently investigated even if it has a low complexity in term of implementation. We consider in this work a cooperative diversity system in which a source transmits some information to a destination with the help of multiple relay nodes with AF protocols and investigate the optimality of allocating powers both at the source and the relays system by optimizing the symbol error rate (SER) performance in an efficient way. Firstly we derive a closedform SER formulation for MPSK signal using the concept of moment generating function and some statistical approximations in high signal to noise ratio (SNR) for the system under studied. We then find a tight corresponding lower bound which converges to the same limit as the theoretical upper bound and develop an optimal power allocation (OPA) technique with mean channel gains to minimize the SER. Simulation results show that our scheme outperforms the equal power allocation (EPA) scheme and is tight to the theoretical approximation based on the SER upper bound in high SNR for different number of relays.

The capacity factor, as a useful tool, was used to characterize the dependence of every link on the capacity changes of a network coding based network. In this paper, we shall investigate the relationship between the network capacity and the set of capacity factors. We firstly introduce a new concept, the capacity kernel, which is a subnetwork deduced from the original network. It will be shown that the capacity kernel of a network maintains most important capacity-related properties of the original network. The capacity kernel can also deduce a projection operator, which to the best of our knowledge, is the first known projection operator acting on the space of all the communication networks. We further introduce and discuss the properties of the C-contra links based on the capacity kernel. As an application, a tighter upper bound on the capacity factor size is then obtained.

In this paper, we analyze the Cramer-Rao lower bound on the accuracy of 3-D emitter locations estimated from a STORM movie with a cylindrical lens. Numerical evaluation for randomly and uniformly distributed emitters indicates that as the emitter density in the image plane increases, the Cramer-Rao lower bounds on the average full-width half-maximum (FWHM) of location estimates in the lateral plane and axial direction increase exponentially fast; and the exponents can be numerically accurately estimated. The Cramer-Rao lower bounds are inversely proportional to the square root of mean number of photons of an emitter and monotonically decrease as the signal to noise ratio increases. The result reveals the insightful property of 3-D STORM movies and provides a benchmark for the achievable accuracy of location estimation algorithms. The developed algorithm with multiemitter colocalization can improve the temporal resolution by five folds compared with the single-emitter location estimator.

In this paper we introduce Integer Quadratic Programming (MIQP) approach to optimally detect QPSK Code Spread OFDM (CS-OFDM) by formulating the problem as a combinatorial optimization problem. The Branch and Bound (BB) algorithm is utilized to solve this integer quadratic programming problem. Furthermore, we propose combined preprocessing steps that can be applied prior to BB so that the computational complexity of the optimum receiver is reduced. The first step in this combination is to detect as much as possible symbols using procedures presented in [9], which is basically based on the gradient of quadratic function. The second step detects the undetected symbols from the first step using MMSE estimator. The result of the latter step will be used to predict the initial upper bound of the BB algorithm. Simulation results show that the proposed preprocessing combination when applied prior to BB provides optimal performance with a significantly reduced computational complexity.

An identification method based on interval analysis for moving forces on cable-stayed bridge with uncertain parameters and noisy measurements is presented. Although there have been many reports on moving force identification methods on bridges, they did not pay much attention to the problem of identifying loads on cable-stayed bridge. And the uncertainties of measurements and bridge parameters were ignored in previous studies. The influence matrix model of cable-stayed bridge was established from the finite element model or in-field test in this study - if using in-field test only, the proposed method will be a model-free method. The upper and lower bound of the identified loads is analyzed based on the interval theory, which is caused by the uncertainties of two kinds: 1) noisy cable tension force measurements; 2) uncertain bridge parameters or influence line test noise. The numerical demonstration and validation are carried out based on Nanjing No.3 Yangtze River Bridge. The main contributions of this paper are: a. to propose an identification method for cable-stayed bridge with uncertain parameters and noisy measurements; b. the location, speed and magnitude of vehicle loads can be estimated simultaneously with the upper and lower bounds.

Image noise is an important aspect when optimizing CT system parameters. For example in multi-energy CT the statistical error in material images is of high interest. It has been shown that the statistical error of individual line integrals can be quantified by the Cramer-Rao lower bound, but it is not straightforward to estimate the noise in the corresponding material images in a time-efficient way, since for an exact calculation a large number of projections has to be taken into account. This paper introduces a way to approximate the image noise by using noise estimates of only a few line integrals. The method is exemplified using simulated dual energy CT data, and the results are shown to closely correspond with Monte Carlo outcomes. The method provides a fast alternative to Monte Carlo simulations in order to calculate the image noise depending on various system parameters, which is very helpful, e.g., for system design.

The electron-multiplying charge-coupled device (EMCCD) is a popular technology for imaging under extremely low light conditions. It has become widely used, for example, in single molecule microscopy experiments where few photons can be detected from the individual molecules of interest. Despite its important role in low light microscopy, however, little has been done in the way of determining how accurately parameters of interest (e.g., location of a single molecule) can be estimated from an image that it produces. Here, we develop the theory for calculating the Fisher information matrix, and hence the Cramer-Rao lower bound-based limit of the accuracy, for estimating parameters from an EMCCD image. An EMCCD operates by amplifying a weak signal that would otherwise be drowned out by the detector's readout noise as in the case of a conventional charge-coupled device (CCD). The signal amplification is a stochastic electron multiplication process, and is modeled here as a geometrically multiplied branching process. In developing our theory, we also introduce a "noise coefficient" which enables the comparison of the Fisher information of different data models via a scalar quantity. This coefficient importantly allows the selection of the best detector (e.g., EMCCD or CCD), based on factors such as the signal level, and regardless of the specific estimation problem at hand. We apply our theory to the problem of localizing a single molecule, and compare the calculated limits of the localization accuracy with the standard deviations of maximum likelihood location estimates obtained from simulated images of a single molecule.

In this paper, we study the performance of the multipath-assisted multitarget tracking using multiframe assignment for initiating and tracking multiple targets by employing one or more transmitters and receivers. The basis of the technique is to use the posterior Cramer-Rao lower bound (PCRLB) to quantify the optimal achievable accuracy of target state estimation. When resolved multipath signals are present at the sensors, if proper measures are not taken, multiple tracks will be formed for a single target. In typical radar systems, these spurious tracks are removed from tracking, and therefore the information carried in such target return tracks are wasted. In multipath environment, in every scan the number of sensor measurements from a target is equal to the number of resolved signals received by different propagation modes. The data association becomes more complex as this is in contrary to the standard data association problem whereas the total number of sensor measurements from a target is equal to at most one. This leads to a challenging problem of fusing the direct and multipath measurements from the same target. We showed in our evaluations that incorporating multipath information improves the performance of the algorithm significantly in terms of estimation error. Simulation results are presented to show the effectiveness of the proposed method.

The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX ‡)at the University of Texas McDonald Observatory will deploy the Visible Integral-Field Replicable Unit Spectrograph (VIRUS) to survey large areas of sky. VIRUS consists of up to 192 spectrographs deployed as 96 units. VIRUS units are fiber-fed and are housed in four enclosures making up the VIRUS Support Structure (VSS). Initial design studies established an optimal array size and an upper and lower bound on their placement relative to the existing telescope structure. Tradeoffs considering IFU (optical fiber) length, support structure mass and ease of maintenance have resulted in placement of four 3 × 8 arrays of spectrograph pairs, about mid-point in elevation relative to the fixed HET structure. Because of the desire to minimize impact on the modal performance of the HET, the VSS is required to be an independent, selfsupporting structure and will only be coupled at the base of the telescope. Analysis shows that it is possible to utilize the existing azimuth drives of the telescope, through this coupling, which will greatly simplify the design and reduce cost. Each array is contained in an insulated enclosure that will control thermal load by means of heat exchangers and use of facility coolant supply. Access for installation and maintenance on the top, front, and rear of the enclosures must be provided. The design and analysis presented in this paper must provide an optimum balance in meeting the stringent requirements for science and facility constraints such as cost, weight, access, and safety.

Recently, there has been considerable interest in the development of robust, cost-effective and high performance non-metallic landmine detection systems using ground penetrating radar (GPR). Many of the available solutions try to discriminate landmines from clutter by extracting some form of statistical or geometrical information from the raw GPR data, and oftentimes, it is difficult to assess the performance of such systems without performing extensive field experiments. In our approach, a landmine is characterized by a binary-valued string corresponding to its impedance discontinuity profile in the depth direction. This profile can be detected very quickly utilizing syntactic pattern recognition. Such an approach is expected to be very robust in terms of probability of detection ( P d ) and low false alarm rates (FAR), since it exploits the inner structure of a landmine. In this paper, we develop a method to calculate an upper bound on the FAR, which is the probability of false alarm per unit area. First, we parameterize the number of possible mine patterns in terms of the number of impedance discontinuities, dither and noise. Then, a combinatorial enumeration technique is used to quantify the number of admissible strings. The upper bound on FAR is given as the ratio of an upper bound on the number of possible mine pattern strings to the number of admissible strings per unit area. The numerical results show that the upper bound is smaller than the FAR reported in the literature for a wide range of parameter choices.

In this paper an algorithm for sniper localization using disparate single microphone sensors that uses only the time difference of arrival (TDOA) between muzzle blast and shock wave is presented. Just as in any algorithm that looks for optimal solution this algorithm also faces the local minima (possible sniper locations) problem. In order to find the global or near global solution one has to perform search over a large area. In order to reduce the computational burden, the search space needs to be small. In this paper, an upper and lower bound on the range for the search space are estimated using the sensor configuration. Based on this, the area around the bullets path is searched with the bounds on range to determine the exact or near global solution for the sniper location. The results of sniper localization algorithm applied to real data collected in a field test will be presented.

Packet-based communication systems, such as Time Division Multiple Access (TDMA) systems, often employ a preamble sequence to allow coarse estimation of carrier frequency offset, phase offset, and signal delay at the receiver. Successful acquisition of these parameters is of critical importance in synchronization and data demodulation. In this work, a simple preamble structure consisting of a continuous wave (CW) signal followed by a unique, continuous phase modulated (CPM) start-of-message (SOM) sequence is analyzed. Simulation results for frequency, phase and timing error are shown to compare favourably with their respective lower bounds. The required CW and SOM sequence lengths are established by statistical analysis of the effect of residual frequency error on symbol timing performance. In particular, it is shown that an iterative peak search of the SOM crosscorrelation nearly achieves the modified Cramer-Rao bound (MCRB) on symbol timing, making it an attractive option for timing acquisition with minimal overhead. In addition, the proposed preamble format and processing approach are compared to that of the MIL-188-181B standard.

Photon counting detectors with energy discriminating capabilities offer the exciting prospect of dose efficient dual energy x-ray imaging. Several techniques have been proposed to form the energy-dependent detector measurements needed for dual energy. However, their performance depends on the limitations of the detectors, an important one being the detector's spectral response. Therefore, in this paper, we study the effect of a detector's spectral response on several dual energy techniques with photon counting detectors. We use a two-parameter model to characterize realistic spectral response functions, which exhibit a Gaussian photopeak trailed by a lower energy tail. The dual energy techniques compared all reduce the spectral data into two measurements using the following methods: (1) binning with an optimally chosen energy threshold; (2) a hybrid photon counting/energy integrating detector; (3) μ-weights, which have been shown to be optimal for ideal detectors. Their performances for different spectral responses are compared by evaluating the Cramer-Rao Lower Bound (CRLB) for estimating the unknown material thicknesses. We show that as the spectral response worsens, μ-weights rapidly deteriorate in performance while a hybrid detector's relative performance improves and consistently outperforms binning. Although the weighting functions are highly sensitive to a detector's spectral response, numerical optimization techniques can find two sets of weights whose performance is close to that of measuring the full detected spectrum.

The impact of the system parameters of the modulator on X-ray scatter correction using primary modulation is studied and an optimization of the modulator design is presented. Recently, a promising scatter correction method for X-ray computed tomography (CT) that uses a checkerboard pattern of attenuating blockers (primary modulator) placed between the X-ray source and the object has been developed and experimentally verified. The blocker size, d, and the blocker transmission factor, α, are critical to the performance of the primary modulation method. In this work, an error caused by aliasing of primary whose magnitude depends on the choices of d and α, and the scanned object, is set as the object function to be minimized, with constraints including the X-ray focal spot, the physical size of the detector element, and the noise level. The optimization is carried out in two steps. In the first step, d is chosen as small as possible but should meet a lower-bound condition. In the second step, α should be selected to balance the error level in the scatter estimation and the noise level in the reconstructed image. The lower bound of d on our tabletop CT system is 0.83 mm. Numerical simulations suggest 0.6 < α < 0.8 is appropriate. Using a Catphan 600 phantom, a copper modulator (d = 0.89 mm, α = 0.70) expectedly outperforms an aluminum modulator (d = 2.83 mm, α = 0.90). With the aluminum modulator, our method reduces the average error of CT number in selected contrast rods from 371.4 to 25.4 Hounsfield units (HU) and enhances the contrast to noise ratio (CNR) from 10.9 to 17.2; when the copper modulator is used, the error is further reduced to 21.9 HU and the CNR is further increased to 19.2.

There have been numerous attempts to determine the channel capacity of a nonlinear fiber optics communication channel. The main approach, until recently, was to consider ASE noise as a predominant effect and to observe the fiber nonlinearities as the perturbation of linear case or as the multiplicative noise. In this invited paper, we describe how to determine the true fiber-optics channel capacity. Because in most of practical applications the channel input distribution is uniform, we also describe how to determine the uniform information capacity, which represents the lower bound on channel capacity. This method consists of two steps: 1) approximating probability density functions (PDFs) for energy of pulses, which is done by one of the following approaches: (a) evaluation of histograms, (b) instanton approach or (c) edgeworth expansion, and 2) estimating information capacities by applying a method originally proposed by Arnold and Pfitser.

For terrestrial free space optical (FSO) systems, we investigate the use of multipulse pulse position modulation (MPPM), which has the advantage of bandwidth efficiency compared to the classical PPM. We first discuss the upper-bound on the information transmission rate for the case of a Gaussian (turbulence-free) channel. We next consider the channel coding issue for MPPM. We propose to use a simple binary convolutional code and to perform iterative soft demodulation and channel decoding at the receiver. We study the performance of this scheme by presenting some numerical results for the cases of Gaussian and weak-turbulence channels. We also show that, in contrast to PPM, the bit-symbol mapping is an important point for MPPM, especially regarding the proposed iterative receiver. In this view, we propose design rules for optimal bit-symbol mapping.

Probability Hypothesis Density (PHD) filter is a unified framework for multitarget tracking and provides estimates for a number of targets as well as individual target states. Sequential Monte Carlo (SMC) implementation of a PHD filter can be used for nonlinear non-Gaussian problems. However, the application of PHD based state estimators for a distributed sensor network, where each tracking node runs its own PHD based state estimator, is more challenging compared with single sensor tracking due to communication limitations. A distributed state estimator should use the available communication resources efficiently in order to avoid the degradation of filter performance. In this paper, a method that communicates encoded measurements between nodes efficiently while maintaining the filter accuracy is proposed. This coding is complicated in the presence of high clutter and instantaneous target births. This problem is mitigated using novel adaptive quantization and encoding techniques. The performance of the algorithm is quantified using a Posterior Cramer-Rao Lower Bound (PCRLB), which incorporates quantization errors. Simulation studies are performed to demonstrate the effectiveness of the proposed algorithm.

This paper is focusing on the influence of the geometry of a multilateration surveillance system onto the accuracy of measuring emitter (target) coordinates regardless of calculation algorithm. Cramer-Rao lower bound concept is used. The way to find an optimal sensors configuration is investigated.

Receiver operating characteristic (ROC) curves provide a means to evaluate the performance of ATR systems. Of specific interest, is the ability to evaluate the performance of fused ATR systems in order to gain information on how well the combined system performs with respect to, for instance, single systems, other fusion methods, or pre-specified performance criteria. Although various ROC curves for fused systems have been demonstrated by many researchers, information regarding the bounds for these curves has not been examined thoroughly. This paper seeks to describe several bounds that exist on ROC curves from fused, correlated ATR systems. These bounds include the lower bound for systems fused using Boolean rules and bounds based on a measure of the variance of the ATR system. Examples using simulated ROC curves generated from correlated and uncorrelated ATR systems will be given as well as a discussion of how correlation affects these bounds. Examining such bounds for a set of candidate fusion rules a priori can focus efforts towards those fused systems that better meet specified ATR system performance criteria.

This paper considers the fault-diagnosis problem for low-degree all-optical networks. Failure-detection schemes which subject to topological constraints are proposed. Optical probe signals are sent in parallel along a set of designed lightpaths. The network health state is derived from the results of this end-to-end test (i.e., probe syndromes). The design objectives are to minimize the diagnosis cost which is represented by the number of probes. We obtain a lower bound of the number of the probes to identify any single link failure and implement this scheme in several networks as well.

The performance of WDM-based coherent time-spreading OCDMA system is studied. Upper bound and lower bound of normalized throughput are obtained with 8 wavelength channels and 127 length and 511 length Gold codes. It is shown that when all simultaneous users are equally allocated to different wavelength channels, WDM+ TS OCDMA has much better performance. However, if there is no central control to allocate wavelength channels equally, WDM+ TS OCDMA system has the in-between performance of normalized throughput.

Capacity allocation(CA) problem modelled by a new method for time-varying traffic is formulated and solved. An upper bound of the capacity saving is given by theoretical analysis. The numerical results show that approximately 25% of the total required capacity can be saved which corresponds to the theoretical analysis.

Due to the availability of cheap passive sensors, it is possible to deploy a large number of them for trackingpurposes in anti-submarine warfare (ASW). However, modern submarines are quiet and dicult to track withpassive sensors alone. Multistatic sensor networks, whi ch have few transmitters (e.g., dipping sonars) in additionto passive receivers, have the potential to improve the t racking performance. We ca n improve the performancefurther by moving the transmitters according to existing target states and any possible new targets. Eventhough a large number of passive sensors are available, due to frequency, processing power and other physicallimitations, only a few of them can be used at any one time. Then the problems are to decide the path of thetransmitters and select a subset from the available passive sensors in order to optimize tracking performance.In this paper, the PCRLB, which gives a lower bound on estimation uncertainty, is used as the performancemeasure. We present an algorithm to decide jointly the optimal path of the movable transmitters, by consideringtheir operational constraints, and the optimal subset of passive sensors that should be used at each time steps fortracking multiple, possibly time-varying, number of targets. Finding the optimal solution in real time is dicultfor large scale problems, and we propose a genetic algorithm based suboptimal solution technique. Simulationresults illustrating the performance of the proposed algorithm are also presented.KEYWORDS: multistatic sensors, path planning, sensor subset selection, multitarget tracking, posteriorCramer-Rao lower bound.

In this paper we analyze the performance limits of multimodal biometric identification systems in the multiple hypothesis testing formulation. For the sake of tractability, we approximate the performance of the actual system by a set of pairwise binary tests. We point out that the attainable error exponent that can be achieved for such an approximation is limited by the worst pairwise Chernoff distance between alternative hypothesis prior models. We consider impact of the inter-modal dependencies on the attainable performance measure and demonstrate that, contrarily to the binary multimodal hypothesis testing framework, an expected performance gain from fusion of independent modalities does not any more play the role of lower bound on the gain one can expect from multimodal fusion.

The problem of joint maximum a posteriori (MAP) bias estimation and data association belongs to a class of nonconvex mixed integer nonlinear programming problems. These problems are difficult to solve due to both the combinatorial nature of the problem and the nonconvexity of the objective function or constraints. A specific problem that has received some attention in the tracking literature is that of the target object map problem in which one tries match a set of tracks as observed by two different sensors in the presence of biases, which are modeled here as a translation between the track states. The general framework also applies to problems in which the costs are general nonlinear functions of the biases. The goal of this paper is to present a class of algorithms based on the branch and bound framework and the "all-pairs" and k-best heuristics that provide a good initial upper bound for a branch and bound algorithm. These heuristics can be used as part of a real-time algorithm or as part of an "anytime algorithm" within the branch and bound framework. In addition, we consider both the A*-search and depth-first search procedures as well as several efficiency improvements such as gating. While this paper focuses on the algorithms, a second paper will focus on simulations.

We analyze the phase and frequency stability requirements of the optical phase reference in a synthetic aperture LADAR imager. There are three distinct frequency regions: (a) "low" frequencies, below the characteristic frequency of the coherent synthetic aperture; (b) "mid" frequencies, up to four times the characteristic frequency of the coherent synthetic aperture; and (c) "high" frequencies, up to and beyond the pulse repetition frequency. The low-frequency requirement is driven by the allowable quadratic phase error, related to the resolution of the impulse response. Mid- and high-frequency requirements are driven by the allowable peak and integrated sidelobe levels. We estimate the upper bound and average PSDs required of the reference oscillator, parametrized by imaging geometry variables such as range, wavelength and synthetic resolution.

We present results from a p-n junction device physics model for GaInP/GaAs/GaInAsP/GaInAs four junction solar cells. The model employs subcells whose thicknesses have an upper bound of 5μm and lower bound of 200nm, which is just above the fully depleted case for the assumed doping of N_A = 1 x 10^(18) cm^(-3) and N_D = 1 x 10^(17) cm^(-3). The physical characteristics of the cell model include: free carrier absorption, temperature and doping effects on carrier mobility, as well as recombination via Shockley-Read-Hall recombination from a single midgap trap level and surface recombination. Upper bounds on cell efficiency set by detailed balance calculations can be approached by letting the parameters approach ideal conditions. However whereas detailed balance calculations always benefit from added subcells, the current matching requirements for series connected p-n multi-junctions indicate a minimum necessary performance from an added subcell to yield a net increase in overall device efficiency. For the four junction cell considered here, optimizing the subcell thickness is an important part of optimizing the efficiency. Series resistance limitations for concentrator applications can be systematically explored for a given set of subcells. The current matching limitation imposed by series connection reduces efficiency relative to independently-connected cells. The overall trend indicates an approximately 5% drop in efficiency for series connected cells relative to identical independently connected cells. The series-connected devices exhibit a high sensitivity to spectral changes and individual subcell performance. If any single subcell within the series-connected device is degraded relative to its optimal design, the entire device is severely hindered. This model allows complex heterostructure solar cell structures to be evaluated by providing device physics-based predictions of performance limitations.

We analyze the performance of a novel detector array for detecting and localizing particle emitting sources. The array is spherically shaped and consists of multiple "eyelets," each having a conical shape with a lens on top and a particle detectors subarray inside. The array's configuration is inspired by and generalizes the biological compound eye: it has a global spherical shape and allows a large number of detectors in each eyelet. The array can be used to detect particles including photons (e.g. visible light, X or γ rays), electrons, protons, neutrons, or α particles. We analyze the performance of the array by computing statistical Cramer-Rao bounds on the errors in estimating the direction of arrival (DOA) of the incident particles. In numerical examples, we first show the influence of the array parameters on its performance bound on the mean-square angular error (MSAE). Then we optimize the array's configuration according to a min-max criterion, i.e. minimize the worst case lower bound of the MSAE. Finally we introduce two estimators of the source direction using the proposed array and analyze their performance, thereby showing that the performance bound is attainable in practice. Potential applications include artificial vision, astronomy, and security.© (2006) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A scheme of WDM+OCDMA system employing optical hard-limiter(OHL) is proposed, and its performance of normalized throughput is analyzed. Upper bound of normalized throughput is obtained when all simultaneous users are equally allocated to different wavelength channels. Lower bound of normalized throughput is obtained when all simultaneous users are firstly allocated to same wavelength channels. Compared with the performance of WDM+OCDMA system without OHL, both upper bound and lower bound of normalized throughput in WDM+OCDMA system with OHL can be improved.

A bandpass optical channel contains four degrees of freedom (DOF) corresponding to two quadrature phase and two quadrature polarization components. If independent information is sent on each of these four components, the spectral efficiency is nearly four times that achieved when utilizing a single component. For a given spectral efficiency, the minimum number of required photons per bit N p diminishes with increasing number of degrees of freedom (DOF), but the lower limit on N p , obtained when the spectral efficiency goes to zero, is 0.693 independent of DOF. For the case of an incoherent channel with square law detection and without polarization filters an upper bound to spectral efficiency and a lower bound to the number of photons per bit is obtained by assuming parallel coherent channels, but in which the same signal is transmitted in each channel. An even tighter bound on performance of the incoherent channel is obtained by computing the mutual information for a specific choice of input distribution utilizing a Markov chain approach.

This paper investigates important properties of acquisition receivers that employ commonly used serial-search strategies. In particular, we focus on the properties of the mean acquisition time (MAT) for wide bandwidth signals in dense multipath channels. We show that a lower bound on the MAT over all possible search strategies is the solution to an integer programming problem with a convex objective function. We also give an upper bound expression for the MAT over all possible search strategies. We demonstrate that the MAT of the fixed-step serial search (FSSS) does not depend on the location of the first resolvable path within the uncertainty region, thereby simplifying the evaluation of the MAT of the FSSS. The results in this paper can be applied to the design and analysis of fast acquisition systems in various wideband scenarios.© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The objective of this paper is to provide an experimental verification of a new H-infinity control scheme on a flexible beam which uses a collocated PZT actuator/sensor pair. We use an analytical bound approach that provides an explicit expression of an upper bound on the H-infinity norm of the closed-loop system and an explicit parametrization of the corresponding output feedback control gains. The method has great computational advantages for large scale structural systems where the solution of H-infinity optimization problems using standard tools could be computationally prohibitive. Both experimental and numerical results are presented that provide a comparison of the performance and the computational requirements on the controller design using the standard H-infinity formulation and the proposed analytical bound approach.

Despite the wide spread need for optical cross-section data on single spore bio-aerosols, available databases are sparse and unreliable. Information reported is based on short path measurements on high concentration media containing particle clusters. This represents an upper bound to the single spore cross-section. Measurements on single spore aerosolized media demand long path lengths and moderate particle concentration. Transmittance measurements need to be in the single scatter limit as well. These requirements are often difficult to meet. We present a procedure that leads to aerosol extinction and backscatter cross-sections in a straightforward manner. Transmittance measurements of thin films of bio-aerosols are used to obtain the bulk refractive index. This result and the measured size distribution can be used in a T-matrix calculation to yield the desired cross-sections. To illustrate this technique, infrared cross-sections are obtained for Bacillus globigii.

Visual signature suppression (VSS) methods for several classes of aircraft from WWII on are examined and historically summarized. This study shows that for some classes of uninhabited aerial vehicles (UAVs), primary mission threats do not stem from infrared or radar signatures, but from the amount that an aircraft visually stands out against the sky. The paper shows that such visual mismatch can often jeopardize mission success and/or induce the destruction of the entire aircraft. A psycho-physioptical study was conducted to establish the definition and benchmarks of a Visual Cross Section (VCS) for airborne objects. This study was centered on combining the effects of size, shape, color and luminosity or effective illumance (EI) of a given aircraft to arrive at a VCS. A series of tests were conducted with a 6.6ft (2m) UAV which was fitted with optically adaptive electroluminescent sheets at altitudes of up to 1000 ft (300m). It was shown that with proper tailoring of the color and luminosity, the VCS of the aircraft dropped from more than 4,200cm2 to less than 1.8cm2 at 100m (the observed lower limit of the 20-20 human eye in this study). In laypersons terms this indicated that the UAV essentially "disappeared". This study concludes with an assessment of the weight and volume impact of such a Visual Suppression System (VSS) on the UAV, showing that VCS levels on this class UAV can be suppressed to below 1.8cm2 for aircraft gross weight penalties of only 9.8%.© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The performance of normalized throughput in WDM+OCDMA system is studied. When all simultaneous users are equally allocated to different wavelength channels, upper bound of normalized throughput is obtained. When all simultaneous users are first allocated to same wavelength channels, lower bound of normalized throughput is obtained. However, if there is no central control to allocate wavelength channels equally, WDM+OCDMA system has the in-between performance of normalized throughput.

A direct detection time-of-flight ladar simulator has been developed to synthesize noisy realizations of true range for the purpose of testing the performance of target recognition algorithms. The simulator can model either peak report or peak report above a threshold using computationally efficient analytic models. In addition, the simulator can also model arbitrary detection logic by direct simulation for cases where analytic models do not exist. Two types of range estimates can occur, local and global. Local errors represent error about the true target range and are described by a Gaussian distribution whose width is given by the Cramer-Rao lower bound. Global errors represent errors that occur because the noise, in one or more bins within the range search interval, is stronger than the target echo. These errors are called "anomalies" and, for peak detection logic, are uniformly distributed over the range search interval. In this paper, the probability density function (PDF) that accounts for both local and global errors is derived. The PDF is a function of signal-to-noise ratio (SNR), range search interval (RSI), and level of speckle diversity. The signal synthesizer uses these PDFs to synthesize the range errors much faster than via direct simulation. Simple approximations to the anomaly probability are derived for high SNRs. The predicted range precision is compared to the results of Monte Carlo simulations of the noisy received signals.

In this paper we consider the general problem of managing an array of sensors in order to track multiple targets in the presence of measurement origin uncertainty. There are two complicating factors: the first is that because of physical limitations (e.g., communication bandwidth) only a small number of sensors can be utilized at any one time. The second complication is that the associations of measurements to targets/clutter are unknown. It is this second factor that extends our previous work [14]. Hence sensors must be utilized in an efficient manner to alleviate association ambiguities and allow accurate target state estimation. Our sensor management technique is then based on controlling the Posterior Cramer-Rao Lower Bound (PCRLB), which provides a measure of the optimal achievable accuracy of target state estimation. Only recently have expressions for multitarget PCRLBs been determined [7], and the necessary simulation techniques are computationally expensive. However, in this paper we propose some approximations that reduce the computational load and we present two sensor selection strategies for closely spaced (but, resolved) targets. Simulation results show the ability of the PCRLB based sensor management technique to allow efficient utilization of the sensor resources, allowing accurate target state estimation.

This paper describes the development of a tool that predicts the coverage and performance of sensor networks. Specifically it examines weapon locating radars and acoustic sensors in different terrain and weather conditions. The computer environment and multiple sensor models are presented. Fusion of sensors takes multiple predicted accuracy metrics from the single sensor performance models and combines them to show networked performance. Calculations include Cramer-Rao lower bound computation of the sensors and the fused sensors source location error. Results are presented showing the outputs of the models in the form of sensor accuracy maps superimposed onto terrain maps.

Based on the proposed polarization mode dispersion (PMD) compensation simulation model and statistical analysis method (Monte-Carlo), the critical parameters initialization of two typical optical domain PMD compensators, which include optical PMD method with fixed compensation differential group delay (DGD) and that with variable compensation DGD, are detailedly investigated by numerical method. In the simulation, the line PMD values are chosen as 3ps, 4ps and 5ps and run samples are set to 1000 in order to achieve statistical evaluation for PMD compensated systems, respectively. The simulation results show that for the PMD value pre-known systems, the value of the fixed DGD compensator should be set to 1.5~1.6 times of line PMD value in order to reach the optimum performance, but for the second kind of PMD compensator, the DGD range of lower limit should be 1.5~1.6 times of line PMD provided that of upper limit is set to 3 times of line PMD, if no effective ways are chosen to resolve the problem of local minimum in optimum process. Another conclusion can be drawn from the simulation is that, although the second PMD compensator holds higher PMD compensation performance, it will spend more feedback loops to look up the optimum DGD value in the real PMD compensation realization, and this will bring more requirements on adjustable DGD device, not only wider adjustable range, but rapid adjusting speed for real time PMD equalization.

In this paper, we build on an established framework for dynamic multi-sensor resource management. The framework is based on the control of the posterior Cramer-Rao lower bound, which provides a bound on the achievable accuracy of target state estimation. We further develop this framework to increase the utility of each sensor by deploying new sensors ahead of the target and in its path. The modified framework is demonstrated in the deployment and utilization of azimuth-only sensors in tracking a single target. Simulation results show that the enhanced strategy is able to accurately track the target while significantly reducing the number of sensors required. However this is at a cost of a significant increase in computation time which may make the technique unsuitable for some sensor management applications.

In this paper, we discuss the Passive Optical Network deployment on an arbitrary grid with guaranteed tolerance towards p -1 equipment failure. We show that this problem in general is NP-hard. We propose an algorithm, which guarantees a solution of 4-approximation to the optimal deployment, and further argue that this is the best lower bound achievable in our case. We do comparative studied with randomized layouts, were our proposed algorithm saves 45% - 55% deployment cost (fiber, equipment, etc.) on average.