Almost instant time inference for hybrid partially dynamic Bayesian networks

A Bayesian network (BN) is a compact representation for probabilistic models and inference. They have been used successfully for many military and civilian applications. It is well known that, in general, the inference algorithms to compute the exact a posterior probability of a target node given observed evidence are either computationally infeasible for dense networks or impossible for general hybrid networks. In those cases, one either computes the approximate results using stochastic simulation methods or approximates the model using discretization or a Gaussian mixture model before applying an exact inference algorithm. This paper combines the concept of simulation and model approximation to propose an efficient algorithm for those cases. The main contribution here is a unified treatment of arbitrary (nonlinear non-Gaussian) hybrid (discrete and continuous) BN inference having both computation and accuracy scalability. The key idea is to precompile the high-dimensional hybrid distribution using a hypercube representation and apply it for both static and dynamic BN inference. Since the inference process essentially becomes a combination of table look-up and some simple operations, the method is shown to be extremely efficient. It can also he scaled to achieve any desirable accuracy given sufficient preprocessing time and memory for the cases where exact inference is not possible     

Recent Breakthroughs in RF Photonics for Radar Systems

Radar systems require transmission of very high purity signals. Photonics is now mature enough to achieve analog transmission with very low noise, strong immunity, and wide-bandwidth even in harsh environments. We present our recent developments of optimized optical links dedicated to radar and multifunction systems     

Two Methods of Spectral Estimation for SARSAT Signals

Search and rescue satellite aided tracking (SARSAT) depends on the processing of emergency locator transmitter (ELT) signals which are received by a satellite in low polar orbit. Since the signal from a distressed vehicle is normally immersed in a background of other ELT signals (false alarms), interference, and noise, different methods of spectral estimation can provide advantages in estimating carrier frequency. A comparison between average spectrum and minimum spectrum for several real signals is provided here.     

Performance evaluation for MAP state estimate fusion

This paper presents a quantitative performance evaluation method for the maximum a posteriori (MAP) state estimate fusion algorithm. Under ideal conditions where data association is assumed to be perfect, it has been shown that the MAP or best linear unbiased estimate (BLUE) fusion formula provides the best linear minimum mean squared estimate (LMMSE) given local estimates under the linear Gaussian assumption for a static system. However, for a dynamic system where fusion is recursively performed by the fusion center on local estimates generated from local measurements, it is not obvious how the MAP algorithm will perform. In the past, several performance evaluation methods have been proposed for various fusion algorithms, including simple convex combination, cross-covariance combination, information matrix, and MAP fusion. However, not much has been done to quantify the steady state behavior of these fusion methods for a dynamic system. The goal of this work is to present analytical fusion performance results for MAP state estimate fusion without extensive Monte Carlo simulations, using an approach developed for steady state performance evaluation for track fusion. Two different communication strategies are considered: fusion with and without feedback to the sensors. Analytic curves for the steady state performance of the fusion algorithm for various communication patterns are presented under different operating conditions.     

Microdosimetric measurements of heavy ion tracks.

The biological effectiveness of radiations depends on the spatial pattern of ionizations and excitations produced by the charged particle tracks involved. Ionizations produced by both the primary ion and by energetic delta rays may contribute to the production of biologically relevant damage and to the concentration of damage which may effect the probability of repair. Although average energy concentration (dose) can be calculated using homogeneous track models, the energy is actually concentrated in small volumes containing segments of the ion and delta ray tracks. These local concentrations are studied experimentally using low pressure proportional counters, and theoretically, using Monte Carlo methods. Small volumes near an ion track may be traversed by a delta ray. If they are, the energy deposited will be similar to that produced by a single electron track in a low-energy x-ray irradiation. The probability of a delta ray interaction occurring decreases with the square of the radial distance from the track. The average energy deposited is the product of this probability and the energy deposited in an interaction. Average energy deposited calculated from measured interaction probability is in good agreement with the results of homogeneous track models.     

Carbon dioxide and oxygen budgets of a plant cultural system in a CELSS--a case of cultivation of lettuce and turnips.

In order to collect basic data about CO2 and O2 budgets of a plant cultural system in a CELSS, the variation of the CO2 absorption rates of lettuce and turnips were observed during the growing period, under different conditions. The O2 release rates were deduced from the CO2 absorption rates multiplied by 32/44. As a result, when the light intensity, the photoperiod and the atmospheric CO2 concentration increased, the rates also increased. The effects on the turnips were more significant than those on the lettuce. Turnips at 310 micromoles/m2/s of PPFD, 24 hours of photoperiod and 1100 ppm of CO2 concentration grew most actively in the present experimental conditions. One turnip absorbed 32.3 g CO2 and released 23.5 g O2 for 6 days between 24 days and 30 days after sowing.     

First estimations of the aerosol optical thickness using Langley Method at Southern Brazil (29.4°S, 53.8°W)

The first estimations of the aerosol optical thickness (AOT) using Langley Method at Southern Space Observatory (SSO) at Southern Brazil (29.4°S, 53.8°W) are presented. In addition to ozone and sulphur dioxide columns, AOT can be obtained using Brewer Spectrophotometer at specific wavelengths: 306.3, 310.1, 313.5, 316.8 and 320.1 nm. The AOT was obtained for the period from November/2002 to May/2003. Very low AOT averages were obtained, whose values were about 0.21 ± 0.03 at 306.3 nm, 0.21 ± 0.02 at 310.1 nm, 0.19 ± 0.02 at 313.5 nm, 0.20 ± 0.02 at 316.8 nm and 0.20 ± 0.02 at 320.0 nm for all period analysed. Different behaviour of AOT were obtained at two daily specific periods of aerosol accumulation, one in the afternoons from November/2002 to February/2003, caused mainly by a mild biomass burning season’s in the region and other in the mornings from March to May/2003, due the high relative humidity presented in the region studied.     

Limits in tracking with extended Kalman filters

The classical linearized conversion of measurements from polar or spherical coordinates to Cartesian ones generates a bias restricting the use of this conversion to cases where the bias can be neglected. In this work, the validity limits for the classical 2D transformation from polar to Cartesian coordinates, as derived in previous work, are shown to be too restrictive and the limits for the 3D transformation from spherical to Cartesian coordinates are introduced. Furthermore, quantitative measures for the performance degradation of the commonly used extended Kalman filter (EKF) in comparison with the best linear unbiased estimation (BLUE) filter are obtained by simulating typical tracking scenarios.     

Solar and Heliospheric Modulation of Galactic Cosmic Rays

The significance of external influences on the environment of Earth and its atmosphere has become evident during recent years. Especially, on time scales of several hundred years, the cosmogenic isotope concentration during the Wolf-, Spoerer-, Maunder- and Dalton-Minimum indicates an increased cosmic ray flux. Because these grand minima of solar activity coincide with cold periods, a correlation of the Earth climate with the cosmic ray intensities is plausible. Any quantitative study of the effects of energetic particles on the atmosphere and environment of the Earth must address their transport to Earth and their interactions with the Earth’s atmosphere including their filtering by the terrestrial magnetosphere. The first problem is one of the fundamental problems in modern cosmic ray astrophysics, and corresponding studies began in the 1960s based on Parker’s cosmic ray modulation theory taking into account diffusion, convection, adiabatic deceleration, and (later) the drift of energetic particles in the global heliospheric magnetic field. It is well established that all of these processes determining the modulation of cosmic rays are depending on parameters that are varying with the solar magnetic cycle. Therefore, the galactic cosmic ray intensities close to Earth is the result of a complex modulation of the interstellar galactic spectrum within the heliosphere. The modern view of this cosmic ray modulation is summarized in our contribution.     

Covariance matrix estimation for adaptive CFAR detection incompound-Gaussian clutter

We address the estimation of the structure of the covariance matrix and its application to adaptive radar detection of coherent pulse trains in clutter-dominated disturbance modeled as a compound-Gaussian process. For estimation purposes we resort to range cells in spatial proximity with that under test and assume that these cells, free of signal components, can be clustered into groups of data with one and the same value of the texture. We prove that, plugging the proposed estimator of the structure of the covariance matrix into a previously derived detector, based upon the generalized likelihood ratio test (GLRT), leads to an adaptive detector which ensures the constant false alarm rate (CFAR) property with respect to the clutter covariance matrix as well as the statistics of the texture. Finally, we show that this adaptive receiver has an acceptable loss with respect to its nonadaptive counterpart in cases of relevant interest for radar applications