In reality, many wireless channels exhibit marked departure from Gaussian noise assumption, causing significant ­performance loss when linear multiuser detectors, which are optimum in the case of Gaussian noise, are used for detection of code division multiple access signals. In this article, we propose a new influence function-based M- estimator and its application to the problem of robust multiuser detection of code division multiple access signals in chaotic modulation systems, in which user data are modulated by an analog chaotic series rather than periodic binary spreading sequences, against non-Gaussian background noise. The solution to this robust detection problem is not in closed form and requires an iterative procedure, which is a limitation in its practical use. However, it causes a little attendant increase in computational complexity in practical applications. Robustness analysis and simulation results show that the proposed detector offers significant performance gains over least-squares and Huber M -estimator-based detectors in chaotic modulation systems in non-Gaussian noise.

The unscented transformation coupled with certain parts of the classic Kalman filter, provides a more accurate ­method than the Extended Kalman Filter for nonlinear state estimation. Using bearings-only measurements, the unscented Kalman Filter algorithm estimates target motion parameters and detects target maneuver, using zero mean chi-square distributed random sequence residuals, in a sliding window format. During target maneuvering, the covariance of the process noise is sufficiently increased in such a way that the disturbance in the solution is minimized. When target maneuver is completed, the covariance of process noise is lowered. The performance of this algorithm is evaluated using Monte Carlo simulation and results are presented.

The effect of a lossy overlay on the read-range of UHF RFID tags is studied. The design of the tag antenna is optimized for long read-ranges and then the effects of a lossy overlay (cover) on its properties are studied. The tags are simulated with and without the lossy overlay material. The input impedance of tag antenna, power transmission coefficient and read-range are calculated and compared for the two cases of with and without overlay. Further, optimization of tag with lossy dielectric overlay is carried out. It is observed that even with the overlay of a lossy dielectric, read-range up to 9 m can be obtained by properly matching the antenna with the RFID IC.

Computational electromagnetics is used to study, design and optimize electromagnetic instruments. This paper introduces function of a magnetic instrument, namely, instrumented pipeline inspection gauge (IPIG), and various computational methods useful for its analysis. Usage of FEMLAB for detailed understanding of magnetic flux leakage (MFL) phenomenon both in 2D and 3D finite element analysis (FEA) is explained. It finally presents a method to perform an important step of defect characterization for IPIG by building large database using FEA tool.

Analytical model equations have been derived from the fundamental principles for effective relative permeability of circular multiple-inclusion magnetic structures like multiple split-ring resonators, spiral resonators and labyrinth resonators, useful for LHM applications. Tailoring of their resonant frequency, their bandwidth and their effective negative permeability is investigated. Thereafter, a suitable structure for operation at millimeter-wave frequency has been explored. When such microstructures are used in a periodic array, the dependence of resonant frequency and bandwidth on the lattice parameter has further been studied.

This article proposes an alternative approach to Tsallis entropy by considering the nonextensive property of ­mammograms. The novel thresholding technique is performed by normalized Tsallis entropy characterized by ­another parameter q, which depends on the nonextensiveness of mammogram. In previous studies, q was calculated using the histogram distribution, which can lead to erroneous results when pectoral muscles were included. In the present study, we propose a new technique to calculate q, which is independent of mammogram grades. We use type-II fuzzy sets to find the optimal value of q. The proposed approach has been tested on various images, and the results have demonstrated that the proposed normalized Tsallis entropy approach outperforms the two-dimensional ­nonfuzzy approach and conventional Shannon entropy partition approach and can be equally effective as Tsallis entropy. ­Moreover, our technique is completely automatic, and trial and error method is avoided as in previous literatures.