For synthetic aperture radar (SAR) systems utilizing a circular aperture for target recognition, it is important to know
how a target's point spread function (PSF) behaves as a function of various radar functional parameters and target
positional changes that may occur during data collection. The purpose of this research is characterizing the three
dimensional (3D) point spread function (3D PSF) behavior of a radially displaced point scatterer for circular synthetic
aperture radar (CSAR). For an automatic target recognition (ATR) systems requiring target identification with a high
degree of confidence, CSAR processing represents a viable alternative given it can produce images with resolution less
than a wavelength. With very large CSAR apertures (90°r; or more) three dimensional imaging is possible with a single
phase center and a single pass. Using a backprojection image formation process, point target PSF responses are
generated at various target locations at a given radar bandwidth, depression angle and full 360°r; CSAR apertures.
Consistent with previous studies, the 3D PSF for a point target located at the image center is cone shaped and serves as
the basis for comparing and characterizing the 3D PSFs for radially displaced scatterers. For radially displaced point
target, simulated results show 3D PSF response is asymmetric and tends to become an elliptic shape.
Single-channel synthetic aperture radar (SAR) can provide high quality, focused images of moving targets by utilizing
advanced SAR-GMTI techniques that focus all constant velocity targets into a three-dimensional space indexed by
range, cross-range and cross-range velocity. However, an inherent geolocation ambiguity exists in that multiple, distinct
moving targets may posses identical range versus time responses relative to a constant velocity collection platform.
Although these targets are uniquely located within a four-dimensional space (x-position, y-position, x-velocity, and y-velocity),
their responses are focused and mapped to the same three-dimensional position in the SAR-GMTI image cube.
Previous research has shown that circular SAR (CSAR) collection geometry is one way to break this ambiguity and
creates a four-dimensional detection space. This research determines the target resolution available in the detection
space as a function of different collection parameters. A metric is introduced to relate the resolvability of multiple target
responses for various parametric combinations, i.e., changes in key collection parameters such as integration time, slant
range, look angle, and carrier frequency.
This paper investigates binary wavefront control in the focal plane to compensate for atmospheric turbulence
in fiber-coupled free-space laser communication (LaserCom) systems. Traditional approaches to turbulence
compensation (i.e., adaptive optics) modify optical phase in the pupil plane to improve the focal plane image
or increase energy on target in the far field. For high-energy laser applications, focal plane phase modulation is
problematic due to high power densities and device damage thresholds. However, LaserCom systems aim to use
minimal power for reasons such as eye safety and covert communication. Thus, focal plane wavefront control is
a reasonable approach for this application. Numerical results show that in an air-to-air scenario, binary phase
modulation provides mean fiber coupling efficiency nearly identical to that resulting from ideal least-squares
adaptive optics, but without the requirement for direct wavefront sensing. The binary phase commands are
derived from a single imaging camera and an assumption about the nature of spot breakup. The use of binary
wavefront control suggests that existing ferro-electric spatial light modulator technology may support real-time
correction. Coupling efficiency results are also compared to those for the Strehl ratio, highlighting the importance
of metric-driven design.
A probabilistic backscatter coefficient generating function (CGF) is introduced which produces realistic backscatter coefficient values for various terrain types over all incidence angles. The CGF was developed in direct support of a multi-layer 3-D clutter modeling effort which successfully incorporated probabilistic clutter reflectivity characteristics and measured terrain elevation data to enhance clutter suppression and improve Signal-to-Clutter Ratio performance in radar applications. This probabilistic clutter modeling approach is in sharp contrast to traditional 2-D modeling techniques which typically include deterministic backscatter characteristics and assume constant terrain features within regions of interest. The functional form and parametric representation of the CGF were empirically determined by comparison with published backscatter data for nine different terrain 'types,' including, soil and rock, shrubs, trees, short vegetation, grasses, dry snow, wet snow, road surfaces, and urban areas. The statistical properties of the output, i.e., the mean and standard deviation, match published measured values to the number of significant figures reported. Likewise, the CGF output frequency of occurrence closely matches measured terrain data frequency of occurrence; a Chi-Square test fails to reject the method at a 0.05 level of significance, indicating a high level of confidence in the results. As developed, the CGF provides a computationally efficient means for incorporating probabilistic clutter characteristics into both simple and complex radar models by accurately reflecting the probabilistic scattering behavior associated with real terrain.
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