The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is an established, first-principles based scene simulation tool that produces synthetic multi-spectral and hyperspectral images from the visible to long wave infrared (0.4 to 20 microns). Over the last few years, significant enhancements such as spectral polarimetric and active Light Detection and Ranging (lidar) models have also been incorporated into the software, providing an extremely powerful tool for algorithm testing and sensor evaluation. However, the extensive time required to create large-scale scenes has limited DIRSIG's ability to generate scenes "on demand." To date, scene generation has been a laborious, time-intensive process, as the terrain model, CAD objects and background maps have to be created and attributed manually. To shorten the time required for this process, we have developed a comprehensive workflow aimed at reducing the man-in-the-loop requirements for many aspects of synthetic hyperspectral scene construction. Through a fusion of 3D lidar data with passive imagery, we have been able to partially-automate many of the required tasks in the creation of high-resolution urban DIRSIG scenes. This paper presents a description of these techniques.
Many hyperspectral sensors collect data using multiple spectrometers to span a broad spectral range. These
spectrometers can be fed by optical fibers on the same or separate focal planes. The Modular Imaging Spectrometer
Instrument (MISI), a 70 band line scanner built by the Rochester Institute of Technology, is configured
in this manner. Visible and near infrared spectrometers at the primary focal plane are each fed by their own
optical fiber. The spatial offset between the two fibers on the focal plane causes an inherent misregistration
between the two sets of spectral bands. This configuration causes a relatively complicated misregistration which
cannot be corrected with a simple shift or rotation of the data. This mismatch between spectral channels has
detrimental effects on the spectral purity of each pixel, especially when dealing with the application of sub-pixel
target detection. A geometric model of the sensor has been developed to solve for the misregistration and achieve
image rectification. This paper addresses the issues in dealing with the misregistration and techniques used to
improve spectral purity on a per pixel basis.
KEYWORDS: LIDAR, Sensors, Data modeling, Image processing, Image fusion, Digital filtering, 3D modeling, 3D image processing, Digital imaging, Image registration
The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is an established, first-principles based scene simulation tool that produces synthetic multispectral and hyperspectral images from the visible to long wave infrared (0.4 to 20 microns). Over the last few years, significant enhancements such as spectral polarimetric and active Light Detection and Ranging (LIDAR) models have also been incorporated into the software, providing an extremely powerful tool for algorithm testing and sensor evaluation. However, the extensive time required to create large-scale scenes has limited DIRSIG's ability to generate scenes "on demand." To date, scene generation has been a laborious, time-intensive process, as the terrain model, CAD objects and background maps have to be created and attributed manually.
To shorten the time required for this process, we are initiating a research effort that aims to reduce the man-in-the-loop requirements for several aspects of synthetic hyperspectral scene construction. Through a fusion of 3D LIDAR data with passive imagery, we are working to semi-automate several of the required tasks in the DIRSIG scene creation process. Additionally, many of the remaining tasks will also realize a shortened implementation time through this application of multi-modal imagery. This paper reports on the progress made thus far in achieving these objectives.
KEYWORDS: Filtering (signal processing), Receivers, Signal to noise ratio, Electronic filtering, Optical filters, Linear filtering, Computer simulations, Digital filtering, Interference (communication), Signal processing
In this paper, the well known notch filtering technique for interference excision in direct sequence spread spectrum communications is expanded, so as to remove the constraint that the instantaneous frequency (IF) of the jammer must be constant over the filter duration. The time-varying difference equation representation of a polynomial phase signal is used to define a new filter impulse response that can effectively remove a y polynomial phase interfering signal. It is shown that thus approach, when applied to jammers with constant modulus property, is more efficient than the existing excision methods implementing notch excision filtering. This paper focuses specifically on chirp signals, and provides both the receiver SNR and bit error rate curves, thus showing the improved performance over similar approaches based on instantaneous frequency information.
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