- Resolution Enhancement for Optical
Nanolithography
Current trends in optical lithography require optical resolution in the
sub-wavelength regimes to enable printing of smaller feature sizes. Some of the
existing approaches toward attaining this goal such are : (a) decreasing the
wavelength, (b) manufacturing lenses with larger numerical apertures and (c)
tighter process control. These
approaches, however, are not without their own problems and their potential for
pushing smaller feature sizes have been more or less exhausted. In these
sub-wavelength regimes, the bandlimitedness of conventional optics attenuates
higher frequencies in the mask (reticle) and this results in a loss of
resolution. Hence the need
for resolution enhancement techniques that will enable sub-wavelength
resolution. Imaging Interferometric lithography (IIL) is one such RET that is
based on a wavelength division multiplexing approach towards the attainment of
the ultimate spatial frequency resolution afforded by optics.
IIL specifically combines off-axis illumination (OAI) with multiple exposures
and pupil plane filtering to implement frequency downshifting of higher
frequencies in the mask so that they can be transmitted through the optical
system without attenuation and then shifted back. For smaller numerical
apertures, the DC frequency term may be lost and a reference beam may need to be
introduced at the pupil plane but for present optical systems with very large
numerical apertures this may not be necessary. In essence, IIL is the optical
equivalent of a modulated filterbank that is commonly used in frequency division
multiple access (FDMA) communication systems. The frequency parsing scheme.
i.e., the division of spatial frequency among the on-axis and off-axis
exposures, used in IIL plays a critical role in terms of resolution and an
improper choice for the relevant parameters may result in undesirable artifacts
in the aerial image. Some of these artifacts in particular will result in
circuit failure in the underlying printed circuit or leakage currents. The
ratios of exposure dosages or energies between the on-axis exposure and the
off-axis exposure or the reference beam
determine the aerial image contrast. Prior IIL experiments have demonstrated the
resolution enhancement capabilities of IIL in isolated parameter settings.
However, a common platform for parameter optimization in IIL that would enable
us to study the resolution limits of IIL is presently lacking.
The goal of the research in this MURI program, funded through a ARO sponsored
grant and performed in collaboration with CHTM, University of New Mexico, is to
develop a common optimization platform and strategies for parameter optimization
as it applies to IIL specifically towards: (a) determining optimal frequency
parsing strategies, (b) establishing performance or error metrics for
optimization, (c) optimization of the exposure energies to obtain optimal aerial
image contrast, (d) optimal use of pupil filtering to alleviate abrupt changes
in the mask error enhancement figure (MEEF), (e) catastrophic error checking to
eliminate undesirable solutions. This project also looks at the application of
this optimization platform in the microscopy problem, i.e., the inverse problem
of IIL, where our goal is to reconstruct the mask image from aerial images of
each exposure obtained via a CCD camera. This optimization platform will enable
the detailed study and comparison of IIL with other RET methods and also enable
the study of IIL based hybrid approaches.
- Cost Effective Solution for Design of DRFM Systems
Existing digital radio frequency memory (DRFM) devices used in radar
systems operate at very high carrier frequency and bandwidth specifications.
Signal processing at these very high data rates is typically done using analog
heterodyning to reduce the processing to a intermediate frequency (IF) and via
custom made A/D and
D/A devices that operate at very high data rates. These devices are considerably
expensive when several of these devices are used in conjunction in a system. The
goal of the research in this project, funded via a grant from the Air force
research labs (AFRL), Kirtland and the Big Crow program, is to develop DSP
hardware
techniques that will allow the use of commercial of the shelf components (COTS)
to design these systems so that they are cost effective. The project
specifically looks at the use of multirate signal processing methods such as
analog-digital hybrid fillterbanks and bandwidth compression using multirate
frequency transformations to (a)
reduce the sampling rate and (b) to compress the bandwidth for reduction of the
sampling rate for subsequent processing. The eventual goal is to develop
guidelines for the design of A/D and D/A devices for very high data rates using
COTS components. The techniques developed here will also be useful in a software
receiver based communications application, specifically in wideband CDMA, where
we need to transform the received signal from passband to a manageable IF.
Design issues considered particularly relevant in radar applications such as
range and velocity gating and cost-effective implementation in a FPGA
environment are considered.
- Signal Environment Analysis
Modern radar systems and both analog/digital communication systems use a wide
variety of modulation techniques to make effective use of power/bandwidth
resources and to combat channel impairments such as fading and multipath. The
problem of determining the type of modulation used in a system, i.e., modulation
classification (MC) is one problem of importance both from a civilian
communications perspective in terms of spectral monitoring and smart receiver
applications and for several military surveillance applications. Existing
methods for solving this problem range from maximum likelihood approaches,
neural network related
approaches, classification based on higher-order statistics, cyclostationarity
based approaches to fuzzy logic based approaches. Each of these approaches has
its own advantage and problems. Neural network based approaches are sensitive to
the training set, require prior knowledge of input statistics and are unable to
adapt
to changes. Approaches that employ higher-order cummulants to maximize a
contrast function to separate the sources that produce the modulated signals
suffer from local minima that do not provide adequate separation between
sources. Approaches that are optimal in a specific sense but not tractable from
a complexity
viewpoint are not desirable.
Machine learning based pattern recognition and
data classification has recently been applied to several communication problems
such as multiuser detection and power control in CDMA systems. These techniques
that include support vector machines (SVM) do not place any restrictions on
statistical characteristics of the input data and are based upon minimizing an
empirical risk. Recently a SVM based approach has been applied towards
classification of modulation types in a radar setting. Specifically, information
theoretic criteria such as mutual information or relative entropy can be applied
to rank/order the features used for classification according to their
importance.
The goal of the research in this AFRL, Kirtland funded project is to first
complete a survey of existing approaches towards solving the MC problem. We also
will look at the application of machine learning based approaches to the more
general problem of signal environment analysis that will determine parameters of
the received signal such as the number of components present, fading, multipath,
bandwidth and modulation type. This will be accomplished by using a combination
of machine learning based methods, cyclic cummulant and cyclic power spectral
density analysis, and feature extraction based on information theoretic
criteria.
- Airline Wire Quality Monitor
The research goal of this project, sponsored by Management Scientific
Inc, was to develop a multisensor approach towards monitoring the quality of
wiring aboard an aircraft. The first step of the project involved a complete
survey of imaging, chemical, electromagnetic, gas, heat and a host of other
sensors that may be applicable to the problem. The second stage of the project
involved data collection and integration of the multisensor data in an
appropriate format into a PDA that can be connected to a network for data
analysis.
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