DOA estimation under unknown mutual coupling and multipath

We propose a new method for direction of arrival (DOA) estimation in the presence of multipath propagation and mutual coupling for a frequency hopping (FH) system. With the use of pilot symbols and assuming perfect time-frequency synchronization for a linear array, we take mutual coupling and multipath propagation into account, and derive a maximum likelihood (ML) estimator for both the mutual coupling matrix and DOA estimation. We then formulate an iterative alternating minimization (AM) algorithm for finding the mutual coupling and DOA parameters in an alternate manner. Simulation results illustrating the performance of the algorithm and comparison with the Cramer-Rao bound (CRB) are also presented.     

Constraints on Coronal Outflow Velocities Derived from UVCS Doppler Dimming Measurements and in-Situ Charge State Data

We constrain coronal outflow velocity solutions, resolved along the line-of-sight, by using Doppler dimming models of H I Lyman alpha and O VI 1032/1037 Å emissivities obtained with data from the Ultraviolet Coronagraph Spectrometer (UVCS) on SOHO. The local emissivities, from heliocentric heights of 1.5 to 3.0 solar radii, were determined from 3-D reconstructions of line-of-sight intensities obtained during the first Whole Sun Month Campaign (10 August to 8 September 1996). The models use electron densities derived from polarized brightness measurements made with the visible light coronagraphs on UVCS and LASCO, supplemented with data from Mark III at NCAR/MLSO. Electron temperature profiles are derived from 'freezing-in' temperatures obtained from an analysis of charge state data from SWICS/Ulysses. The work concentrates on neutral hydrogen outflow velocities which depend on modeling the absolute coronal H I Lyα emissivities. We use an iterative method to determine the neutral hydrogen outflow velocity with consistent values for the electron temperatures derived from a freezing-in model.     

Background noise suppression for signal enhancement by noveltyfiltering

The enhancement of weak signals in the presence of background and channel noise is necessary to design a robust automatic signal detection and recognition system. The autoassociative property of neural networks can be used to map the identifying characteristics of input source waveforms or their spectra. This paper is directed at the exploitation of such neural network properties for novelty filtering that improves the detection probability of weak signals by learning and subsequent subtraction of noise background from the input waveform. A neural-network-based preprocessor that learns to selectively filter out the background noise without significantly affecting the signal will be highly useful in solving practical signal enhancement problems. An analytical basis is established for the operation of neural-network-based novelty filters that enhance the signal detectability in the presence of noise background and channel noise     

A fast adaptive null-steering algorithm based on output powermeasurements

Presented and investigated here is a simple and fast adaptive algorithm for linear power inversion arrays whose nulls can be accurately steered by controlling the element weights. Based on measurements of the powers of the three signals derived from the array output and the output of an auxiliary beamformer, the algorithm tracks unknown jammers in the environment by steering the nulls of the array one by one in a cyclical time-multiplexed manner. When compared with the least mean square (LMS) algorithm, the proposed algorithm has about the same implementation complexity, a better convergence behavior and the advantage that nulls are directly available     

Data association for deghosting in Y-shaped passive linear array sonars

This paper deals with data association using three sets of passive linear array sonars (PLAS) geometrically positioned in a Y-shaped configuration, fixed in an underwater environment. The data association problem is directly transformed into a 3D assignment, which is known to be NP hard. For generic passive sensors, it can be solved using conventional algorithms, while in PLAS, it becomes a formidable task due to the presence of bearing ambiguity. Thus, the central issue of the problem in PLAS is how to eliminate the bearing ambiguity without increasing tracking error. To solve this problem, the 3D assignment algorithm used the likelihood value of only those observed bearing measurements is modified by incorporating frequency information in consecutive time-aligned scans. The region of possible ghost targets is first established by the geometrical relation of PLAS with respect to target. The ghost targets are then confirmed and eliminated by generating multiple observations in consecutive scans. Representative simulations demonstrate the effectiveness of the proposed approach.     

Divisible load scheduling on single-level tree networks with buffer constraints

Scheduling a divisible load on a heterogeneous single-level tree network with processors having finite-size buffers is addressed. We first present the closed-form solutions for the case when the available buffer size at each site is assumed to be infinite. Then we analyze the case when these buffer sizes are of finite size. For the first time in the domain of DLT (divisible load theory) literature, the problem of scheduling with finite-size buffers is addressed. For this case, we present a novel algorithm, referred to as incremental balancing strategy, to obtain an optimal load distribution. Algorithm IBS adopts a strategy to feed the divisible load in a step-by-step incremental balancing fashion by taking advantage of the available closed-form solutions of the optimal scheduling for the case without buffer size constraints. Based on the rigorous mathematical analysis, a number of interesting and useful properties exhibited by the algorithm are proven. We present a very useful discussion on the implications of this problem on the effect of sequencing discussed in the literature. Also, the impact of Rule A, a rule that obtains a reduced optimal network to achieve optimal processing time by eliminating a redundant set of processor-link pairs, is also discussed. Numerical examples are presented.     

Direct Energy Transfer for High Efficiency Photovoltaic Energy Systems Part II: Experimental Evaluations

This two-part paper presents a comprehensive comparative study on parallel power processing (PPP) and standard schemes in dc/dc converters for photovoltaic (PV) energy systems. It is demonstrated how PPP can improve direct energy transfer (DET), which results in PV systems operating at higher voltage and efficiency. Discussions of the concepts, hypotheses, and computer simulations are presented in Part I. Part II provides the experimental results, which confirm the validity of the analysis and simulations.     

Generation of satellite tracking profile: Problems and validation algorithms

Recently, as a satellite mission becomes complicated, it has been required to generate the schedule of satellite antenna movements automatically without relying upon operator’s ad hoc knowledge. To generate the satellite antenna schedule autonomously, this paper first addresses geometrical problems associated with the antenna scheduling and mission planning problems that can be formulated from satellite navigation and antenna orientation information. Then, based on the solutions of the geometrical problems, a set of antenna azimuth and elevation angles that enables the antenna to point towards the desired ground station is obtained systematically. Using the computed azimuth and elevation angles, the satellite tracking profile (TP) is generated, and to validate it, TP validation algorithms are developed.     

Material optimization: bridging the gap between conceptual and preliminary design

This paper presents a collection of tools for conceptual structure design. The underlying model is the ‘free material optimization’ problem. This problem gives the best physically attainable material and is considered as a generalization of the sizing/shape optimization problem. The method is supported by powerful optimization and numerical techniques, which allow us to work with bodies of complex initial design and with very fine finite-element meshes. The computed results are realized by composite materials. We consider a particular class of fibre-reinforced composite materials, manufactured by the so-called tape-laying technology. In the post-processing phase, stress/strain-trajectories are plotted which indicate how to place these tapes; they also show the proposed thickness of the tapes. Several examples demonstrate the efficiency of this approach to conceptual design of engineering structures.