Parametric Rao Test for Multichannel Adaptive Signal Detection

The parametric Rao test for a multichannel adaptive signal detection problem is derived by modeling the disturbance signal as a multichannel autoregressive (AR) process. Interestingly, the parametric Rao test takes a form identical to that of the recently introduced parametric adaptive matched filter (PAMF) detector for space-time adaptive processing (STAP) in airborne surveillance radar systems and other similar applications. The equivalence offers new insights into the performance and implementation of the PAMF detector. Specifically, the Rao/PAMF detector is asymptotically (for large samples) a parametric generalized likelihood ratio test (GLRT), due to an asymptotic equivalence between the Rao test and the GLRT. The asymptotic distribution of the Rao test statistic is obtained in closed form, which follows an exponential distribution under the null hypothesis H ₀ and, respectively, a noncentral Chi-squared distribution with two degrees of freedom under the alternative hypothesis H ₁. The noncentrality parameter of the noncentral Chi-squared distribution is determined by the output signal-to-interference-plus-noise ratio (SINR) of a temporal whitening filter. Since the asymptotic distribution under H ₀ is independent of the unknown parameters, the Rao/PAMF asymptotically achieves constant false alarm rate (CFAR). Numerical results show that these results are accurate in predicting the performance of the parametric Rao/PAMF detector even with moderate data support.     

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     

A method for constructing an airfoil using a specified chord velocity diagram

A problem of determining a shape of the airfoil being streamlined by a potential incompressible inviscid flow is solved by the successive approximation method using a specified chord velocity diagram. It is shown that a closed airfoil that possesses a specified chord velocity diagram can be constructed with a sufficient accuracy; if the chord diagram is unsuccessfully specified, the closed airfoil may prove to be not univalent, that is, physically unrealizable.     

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.     

Spiral evolution applied to legacy avionics systems

The US Department of Defense (DoD), through the Office of the Secretary of Defense (OSD), has determined that evolutionary acquisition is their strategy of choice for future software-intensive systems, and that the spiral development model (SDM) is the preferred method/process for software-intensive development life cycles. Electronic Systems Command (ESC) at Hanscom AFB, Massachusetts, has written a draft handbook on the use of Spiral Development for all future Command and Control (C2) systems, including reference to the DoD 5000 series and Air Force Program Directive 63-1, Acquisition System, which deploys this OSD mandate for future C2 systems. Barry Boehm's continued work on SDM which he conceived in the 1980s, is heavily biased toward development of new systems that are software-intensive, as noted in a workshop he gave at the Software Engineering Institute (SEI) in 2000.     

Automotive-grade MEMS sensors used for general aviation

The attitude heading reference system (AHRS) provides data for primary flight instruments, head-up displays, autopilots, and moving map navigation systems. Advances in solid-state MEMS rate sensors, coupled with Kalman filter algorithms designed to mitigate high drift rates, provide the basis for low-cost, high-performance AHRS for general aviation. This paper describes the performance of a low cost, miniaturized AHRS using automotive-grade MEMS sensors. The performance of the system is detailed. The implications for certification of this class of system and fault tolerance are discussed.     

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.     

Design for validation

An approach is outlined for the development of ultrareliable avionics for civil air transports using a design-for-validation philosophy that includes rigorous application of formal methods. The basic concept of the methodology is introduced, and the role of formal methods is explored. The impact of the design-for-validation philosophy on the system design process is then demonstrated by two simple examples. More details about the design-for-validation methodology are then given     

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.