Fiber optic fence sensor developments

Many detection technologies have been employed for perimeter detection, to sensitize a barrier. These outdoor perimeter fence detection sensors must reliably detect intruders attempting to cut or climb the barrier, while ignoring the effects of environmental noise, including nearby activity. In recent conference proceedings, the new IntelliFIBER/spl trade/ fiber optic based product was introduced and compared with previous technologies. IntelliFIBER is designed to provide the advantages of a nonconductive "dielectric" cable sensor, e.g., resistance to electromagnetic interference and the ability to provide longer cable zones. It utilizes the proven processor of the Intelli-FLEX/spl trade/ triboelectric cable fence sensor, which provides relay or bidirectional networked serial communications and is compatible with its calibration module. IntelliFIBER also capitalizes on the Intelli-FLEX's adaptive detection algorithms that were developed through extensive field-testing, to provide exceptional immunity to environmental alarms while still detecting the skilled intruder.     

Analysis of shells of revolution under symmetrical loading using the quadrature method

The application of the quadrature method [1] to analyzing the shells of revolution under symmetrical loading relative to the zero meridian is considered. The method can be treated as a generalization of the method presented in [2] to solve the Volterra integral equation of the second kind.     

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.     

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.     

HMS SCOTT ring laser gyro navigator integration

HMS SCOTT is a United Kingdom ocean survey vessel that hosts a state-of-the-art deep ocean mapping system which was designed, developed, and is currently maintained and periodically updated by the Space and Naval Warfare Systems Center, San Diego, (SSC San Diego). A recent update of this system consisted of the replacement of an obsolete and very costly to maintain inertial navigation system. Another reason for updating the ship's inertial system was to provide higher accuracy attitude data, than was previously available with the old inertial system, to the high resolution multi-beam sonar system in order to produce improved bathymetric charts. After conducting a market survey of suitable inertial navigator systems, the Kearfott SEANAV ring laser gyro navigator (RLGN) system, using a monolithic T-24 gyro, was selected to replace the old inertial system. The selection of the SEANAV RLGN was based on its relatively low cost, high reliability, and, particularly, the roll and pitch data accuracies of typically less than 1-arc-minute. This attitude data accuracy was key to enable a significant improvement in the bathymetry data accuracy. Two SEANAV systems were integrated with GPS receivers, a system master time code generator, and electro magnetic (EM) log and Doppler sonar speed sensors to provide the navigation portion of the mapping data. Operational testing of this updated system aboard HMS SCOTT, in November, 2003, showed a marked improvement in the quality of the map product due, in part, to the improved attitude data provided by the SEANAV RLGN system.     

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.     

Reduced-order multiple model adaptive controller for flexiblespacestructure

The robustness of a moving-bank multiple model adaptive estimator/controller to order reduction in the controller design model is examined. It is shown that the adaptive mechanism and bank-moving logic are not confounded by the effects of unmodeled higher order modes of a large flexible spacestructure. Control characteristics are achieved that are essentially equivalent to those of an artificially informed benchmark controller