In this paper we propose and analyze a step-index optical fiber design in which normalized frequency, V, remains constant at all wavelengths of interest. Such a fiber would require materials with specific wavelength dependent refractive index profile. Constant-V operation ensures that the effective area becomes wavelength independent. Larger core with higher V ensures that fiber can have larger effective area, high confinement factor, and reasonably lower bendloss. Such fibers will exhibit higher local dispersion, which is desirable for DWDM communications.
In this paper we present a control channel-based modular switching technique for packet transport over next-generation high-speed dense- wavelength division multiplexed (DWDM) networks. The proposed technique reduce electronic processing bottleneck in DWDM networks by sending routing information on a dedicated control channel in the form of pilot control packets. The pilot control packets are processed electronically by a control processor at each intermediate node. Processing of pilot control packets ensures that the data packets propagate from source to destination in photonic form (that is, without any processing by intermediate nodes). In the proposed switch, different modules perform different functions. The modular nature of the proposed switch enables that each module can be implemented in any available technology. Thus, with the technology improvements, individual modules can be upgraded as compared to replacing the whole switch. The performance evaluations of the proposed technique show that 3x reduction in processing requirements can be achieved for a 100 channel DWDM-based long haul network. This reduction in processing requirements translates into 2x reduction in hardware cost. Furthermore, the proposed technique provides a large saving in terms of electrical-to-optical and optical-to-electrical converters cost per node. This saving in processing reduction can be leveraged to provide more bandwidth to the services.
We present a new method for estimating the motion parameters of a target from its inverse synthetic aperture radar (ISAR) signature. This method uses the phase of the target's echo transfer function to calculate a focal quality indicator while avoiding two-dimensional Fourier processing. The focal quality indicator reaches the global minimum of a parametric motion surface when the phase is compensated with the target's actual motion parameters. The presence of an absolute minimum without local minima guarantees that the estimated motion parameters are an accurate representation of the target's motion and allows the use of a simple search procedure. Polynomial fitting is incorporated to the new method to improve the robustness by reducing estimation errors due to the finite order of the parametric motion model.
In this article, we present a method for estimating the translational motion parameters of a target from its ISAR signature. The method exploits the phase of the target's frequency response and does not require 2D Fourier processing. The basis for this method is a phase difference indicator which converges to an absolute minimum when the phase is compensated with the true values of the motion parameters. The analysis of the phase difference indicator leads to an algorithm for motion parameter optimization. Processing of simulated and experimental ISAR signatures demonstrates that the phase difference method is extremely computationally efficient and equally accurate when compared to robust techniques based on entropy or Fisher information indicators.
In this paper we formalize a theory for indicators designed to focus ISAR imagery of non-cooperative targets. These indicators represent variations of the Fisher information and entropy measures, and are capable of operating either in the spatial-frequency domain or in the spatial domain. This freedom of choice is advantageous since the information on the target's representation in either domain has phase and magnitude components, which can be efficiently exploited to resolve and focus the target's primary elements. These elements are displayed as radar cross section (RCS) distribution, we propose a phase correction algorithm based on parametric models of a target's temporal maneuvers. The approach is to quantify the phase non-linearities via the Fisher information or entropy measure that is dependent on motion parameter estimates. The optimization of these parameter estimates is a m-dimensional search problem that minimizes the focus quality indicator over a prescribed tolerance for a given SNR. The coordinates of this minimum point are subsequently used to generate a phase correction factor that eliminates image blurring, thus providing better focusing for effective target recognition.
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