On-board statistical detection and compensation of anomalous pilot-aircraft interactions

A statistical method for the on-board detection and compensation of adverse oscillations in pilot-aircraft systems is presented. A recursively updated linear model representing the pilot-aircraft system is used to continuously check for stability loss. The instability-related oscillations are detected early, using a statistical hypothesis test. Furthermore, a specially designed stability augmentation system assists the pilot during the instability periods. The method's effectiveness is demonstrated via data obtained from a flight simulator and a detailed simulation model.     

Robust wavelet neuro control for linear brushless motors

Design, simulation and experimental implementation of a wavelet basis function network learning controller for linear brushless dc motors (LBDCM) are considered. Stability robustness with position tracking is the primary concern. The proposed controller deals mainly with external disturbances, e.g. nonlinear friction force and payload variation in motion control of linear motors. It consists of two parts, one is a state feedback component, and the other one is a learning feedback component. The state feedback controller is designed on the basis of a simple linear model, and the learning feedback component is a wavelet neural controller. The attenuation effect of wavelet neural networks on friction force is first verified by the numerical method. The learning effect of wavelet neural networks on friction force is also shown in the numerical results. Then, a wavelet neural network is applied on a real LBDCM to on-line suppress the friction force, which may be variable due to the different lubrication. The effectiveness of the proposed control schemes is demonstrated by simulated and experimental results.     

Advances in signal processing technology for electronic warfare

The denial of effective communications by enemy forces during hostile military operations has been a primary concern for military commanders since the inception of radio communications on the battlefield before World War II. Since then, the electromagnetic environment has been in a constant state of evolution toward more sophisticated jam-resistant and convert forms of modulation. For example, exotic modulation techniques employing spread spectrum (SS) signaling are routinely used by our adversaries to provide their communication links an advantage over US and Allied jammers. These same spread spectrum modulation techniques are being refined to provide convert, low probability-of-intercept (LPI) features to the unintended interceptor. The thrust of this paper focuses on developments in the theory and algorithms for detection, characterization, and exploitation of advanced waveforms using new mathematical signal processing tools. Specifically, quadratic time-frequency signal representations, wavelet transforms, and cyclostationary signal processing are introduced. This overview demonstrates the importance of these advanced techniques in a clear and concise manner. Applications and future research activities are described     

Sequences and arrays with perfect periodic correlation

Properties and methods for synthesizing sequences with perfect periodic autocorrelation functions and good energy efficiency are discussed. The construction is extended to two-dimensional perfect arrays. The construction methods used are based mainly on a search in the frequency domain and on a multiplication theorem for periodic sequences and arrays     

Temporal decorrelation of X-band backscatter from wind-influencedvegetation

The temporal decorrelation characteristics of X-band radar backscatter from wind-influenced vegetation were investigated using a short-range CW radar. Radar reflectance data were gathered on various types of individual trees from a distance of approximately 30 m. The windspeed was monitored during each measurement, which lasted 5 s. The crown cover and the mean leaf area of the trees were also recorded. Autocovariance plots were generated for each measurement, from which the decorrelation time was estimated. As expected, the return signals decorrelated faster at higher wind speeds. However, the decorrelation time was also found to depend on the tree type, tree structure, and leaf cover characteristics. Measured decorrelation times for moderate winds (7-9 m/s) were often between 40-60 ms, although the lowest decorrelation time measured under these conditions was 14 ms for the Eastern Cottonwood. In lighter winds (1-4 m/s), decorrelation times were much longer, and there was substantial spread in the data     

Prebiotic oligodeoxynucleotide synthesis in a cyclic evaporating system at low temperatures.

Deoxynucleoside 5'-monophosphates were condensed by cyanamide or by l-ethyl-3-(3-dimethylaminopropyl) carbodiimide in the presence of ammonium chloride at 0 degree, 37 degrees or 60 degrees C through several cycles of evaporation to dryness with replenishment of all reactants at each cycle. We found that at 37 degrees or 60 degrees cyanamide gives distinctly more high molecular weight material than does carbodiimide. Indeed, the yield of condensed products for the cyanamide reaction (dimers and higher oligomers) was found to be between 60 percent and 80 percent. The molecular weight distribution of the product shifts to higher molecular weights as cycling continues at 37 degrees or 60 degrees for both condensing agents. The water soluble carbodiimide gives higher yields of low molecular weight product but much lower yields of the higher molecular weight products. At 0 degree yields of high molecular weight product were low for both condensing agents. Results of characterization of the products demonstrate the synthesis of oligodeoxynucleotides including tetramers, with 3'-5' phosphodiester linkages.     

Visual thematic mapping from Landsat and collateral data in support of mineral development

Over the past ten years, the authors and their associates have used Landsat images and collateral data to prepare visual thematic maps. The data are used in a projection-compositor (Procom) system that enlarges Landsat images and other data to scales as great as 1:15 000. Revisions of existing maps for simple themes (e.g. topographic maps) can be completed quickly, accurately and inexpensively. Complex themes, such as geological formations and structures, can be mapped through the optical merging of collateral data sets (e.g. Landsat, geophysics, geology) at a common scale. Such mapping has led to the recognition of a non-parallactic means of obtaining whole image stereo-models with large vertical exaggerations using Landsat images.     

Multiple moving target detection and trajectory estimation using a single SAR sensor

A novel methodology is presented for determining the velocity and location of multiple moving targets using a single strip-map synthetic aperture radar (SAR) sensor. The so-called azimuth position uncertainty problem is therefore solved. The method exploits the structure of the amplitude and phase modulations of the returned echo from a moving target in the Fourier domain. A crucial step in the whole processing scheme is a matched filtering, depending on the moving target parameters, that simultaneously accounts for range migration and compresses two-dimensional signatures into one-dimensional ones without losing moving target information. A generalized likelihood ratio test approach is adopted to detect moving targets and derive their trajectory parameters. The effectiveness of the method is illustrated with synthetic and real data covering a wide range of targets velocities and signal-to-clutter ratios (SCRs). Even in the case of parallel to platform moving target motion, the most unfavorable scenario, the proposed method yields good results for, roughly, SCR > 10 dB.     

PMHT: problems and some solutions

The probabilistic multihypothesis tracker (PMHT) is a target tracking algorithm of considerable theoretical elegance. In practice, its performance turns out to be at best similar to that of the probabilistic data association filter (PDAF); and since the implementation of the PDAF is less intense numerically the PMHT has been having a hard time finding acceptance. The PMHT's problems of nonadaptivity, narcissism, and over-hospitality to clutter are elicited in this work. The PMHT's main selling-point is its flexible and easily modifiable model, which we use to develop the "homothetic" PMHT; maneuver-based PMHTs, including those with separate and joint homothetic measurement models; a modified PMHT whose measurement/target association model is more similar to that of the PDAF; and PMHTs with eccentric and/or estimated measurement models. Ideally, "bottom line" would be a version of the PMHT with clear advantages over existing trackers. If the goal is of an accurate (in terms of mean square error (MSE)) track, then there are a number of versions for which this is available.     

Advanced optical processors for multiple degree-of-freedom objectrecognition

Several optical pattern recognition techniques suitable for multiple-degree-of-freedom object recognition are described. These include a correlator, an associate processor, and three feature extractors using moments, chord distributions, and a space-variant feature space. The processing architectures, the algorithm details, and initial results obtained for each approach are presented