Application of Kalman filtering to the calibration and alignment ofinertial navigation systems

The development of Kalman filters for the calibration and alignment of complex inertial guidance systems is presented. The attitude error equation is augmented by gyro and accelerometer model parameters. The mechanization of the algorithm involves preprocessing the raw measurements to reduce the computational load. Results for simulated data show that preprocessing has very little effect on the performance of the filter. Other topics discussed include gyro and accelerometer models and a technique for generating parameter excitation trajectories     

Quantitative NMR spectroscopy using coaxial inserts containing a reference standard: purity determinations for military nerve agents.

A novel 31P NMR method for the determination of purity for the military nerve agents sarin, soman, and VX has been developed. In contrast to more conventional quantitative NMR methods, stem coaxial inserts are placed into the sample tube to introduce reference material into the analysis without mixing or reaction with the analyte. All sample preparation is eliminated, and the analysis is completed expeditiously in less than 25 min. The method is highly specific and rugged with respect to operator-induced variability, experimental parameters, and all influences from nuclear magnetic relaxation. Nerve agent purity can be determined with a precision and accuracy typically better than 1%, and impurities can be detected at concentrations as low as 25 microg/mL. The limit of quantitation has been estimated at 85 microg/mL. In terms of precision, accuracy and execution time, the method rivals typical chromatographic methods.     

Organizing spatial data for robotics systems

Successful robotics systems require the organization and analysis of a tremendous amount of sensor data. Moreover, the current computer paradigm of “shape-from” algorithms requires multi-dimensional data from the sensors, e.g. 3-space location and surface normal. Such multi-dimensional vectors must be organized such that spatial searching is efficient and so that spatial proximity is easily determined. Unfortunately, even though methods of computational geometry have been quite successful in dealing with intersection and proximity problems in 2-D, they have not been so successful in dealing with data of dimension greater than two. We define the spatial proximity graph as a low-level organizational structure, and show how it can be built efficiently. Some examples are given.     

Some recent developments in microstrip antenna design

The fundamental radiation mechanism occurring at an open-circuit discontinuity is discussed to reveal limitations on bandwidth, efficiency, and sidelobe level control inherent in microstrip antennas, based on resonator action. Extraneous radiation from feed transitions is also assessed and shown to be a problem in some cases. Novel two-dimensional arrays using resonant elements are described which illustrate these performance limitations. In contrast, a nonresonant circularly polarized spiral element has a very wide bandwidth at the expense of lower efficiency. Other designs are then noted to show how a particular parameter or aspect can be optimized for antenna applications demanding choice of polarization, frequency scanning, log periodic behavior, low angle radiation, and integration with circuitry on a common substrate.     

The specification of distributed sensing and control

Logical Sensor System Specification (LSS) has been introduced as a convenient means for specifying multi-sensor systems and their implementations. In this article we demonstrate how control issues can be handled in the context of LSS. In particular, the Logical Sensor Specification is extended to include a control mechanism which permits control information to (1) flow from more centralized processing to more peripheral processes, and (2) be generated locally in the logical sensor by means of a micro-expert system specific to the interface represented by the given logical sensor. Examples are given including a proposed scheme for controlling the Utah/MIT dextrous hand.     

Elastodynamic response of a coplanar periodic layer of elastic spherical inclusions

Reflection and transmission spectra of a plane longitudinal wave normally incident on a coplanar periodic array of identical spherical elastic inclusions in a solid (polyester) matrix are measured at wavelengths that are comparable to the inter-particle distance. These spectra exhibit pronounced Wood's anomalies i.e., a sharp variations in amplitude at the onset of a shear wave diffraction order as well as a drop in the transmission and a corresponding maximum in the reflection coefficients due to an enhancement of the resonance of the particles (for the case reported herein, this is the rigid body translational “dipole” resonance). An approximate low frequency (ka<1) self-consistent model is developed in which multiple scattering is explicitly taken into account by adding appropriate terms to the well-known solution for the scattering of a plane longitudinal wave by a single spherical particle in an unbounded matrix. The results of the numerical calculations show excellent agreement with the experimental data.     

Influence of antidepressant pharmacotherapy on behavioral treatment adherence and smoking cessation outcome in a combined treatment involving fluoxetine.

The authors examined whether serum fluoxetine levels influence behavioral treatment adherence and smoking cessation outcome. Nondepressed smokers (N?=?989) from 16 centers were randomized on a double-blind basis to receive either fluoxetine (30 or 60 mg) or placebo plus 9 sessions of behavioral smoking cessation treatment. Fluoxetine and norfluoxetine blood levels were assayed 1 week after the quit date. Logistic regression was used to predict treatment completion and cessation outcome, controlling for gender, age, treatment site, and degree of nicotine dependence. Higher steady-state fluoxetine blood levels (fluoxetine?+?norfluoxetine) predicted less likelihood of dropping out, χ2(1, N?=?820)?=?3.9, p?N?=?513)?=?18.1, p?     

Incremental syntactic parsing of natural language corpora withsimple synchrony networks

The article explores the use of Simple Synchrony Networks (SSNs) for learning to parse English sentences drawn from a corpus of naturally occurring text. Parsing natural language sentences requires taking a sequence of words and outputting a hierarchical structure representing how those words fit together to form constituents. Feedforward and simple recurrent networks have had great difficulty with this task, in part because the number of relationships required to specify a structure is too large for the number of unit outputs they have available. SSNs have the representational power to output the necessary O(n²) possible structural relationships because SSNs extend the O(n) incremental outputs of simple recurrent networks with the O(n) entity outputs provided by temporal synchrony variable binding. The article presents an incremental representation of constituent structures which allows SSNs to make effective use of both these dimensions. Experiments on learning to parse naturally occurring text show that this output format supports both effective representation and effective generalization in SSNs. To emphasize the importance of this generalization ability, the article also proposes a short-term memory mechanism for retaining a bounded number of constituents during parsing. This mechanism improves the O(n²) speed of the basic SSN architecture to linear time, but experiments confirm that the generalization ability of SSN networks is maintained