Modeling space-based multispectral imaging systems with DIRSIG

Abstract

The Landsat Data Continuity Mission (LDCM) focuses on a next generation global coverage, imaging system to replace the aging Landsat 5 and Landsat 7 systems. The major difference in the new system is the migration from the multi-spectral whiskbroom design employed by the previous generation of sensors to modular focal plane, multi-spectral pushbroom architecture. Further complicating the design shift is that the reflective and thermal acquisition capability is split across two instruments spatially separated on the satellite bus. One of the focuses of the science and engineering teams prior to launch is the ability to provide seamless data continuity with the historic Landsat data archive. Specifically, the challenges of registering and calibrating data from the new system so that long-term science studies are minimally impacted by the change in the system design. In order to provide the science and engineering teams with simulated pre-launch data, an effort was undertaken to create a robust end-to-end model of the LDCM system. The modeling environment is intended to be flexible and incorporate measured data from the actual system components as they were completed and integrated. The output of the modeling environment needs to include not only radiometrically robust imagery, but also the meta-data necessary to exercise the processing pipeline. This paper describes how the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model has been utilized to model space-based, multi-spectral imaging (MSI) systems in support of systems engineering trade studies. A mechanism to incorporate measured focal plane projections through the forward optics is described. A hierarchal description of the satellite system is presented including the details of how a multiple instrument platform is described and modeled, including the hierarchical management of temporally correlated jitter that allows engineers to explore impacts of different jitter sources on instrument-to-instrument and band-to-band registration. The capabilities of a new, non-imaging instrument to simulate the measurement of platform ephemeris is also introduced. Finally, the geometric and radiometric foundations for modeling clouds in the DIRSIG model will be described and demonstrated as one of the more significant challenges in registering multi-spectral pushbroom sensor data products.

Stray Light Artifacts in Imagery from the Landsat 8 Thermal Infrared Sensor

“…The DIRSIG software is a physics-based synthetic image generation tool developed at the Rochester Institute of Technology (RIT) that utilizes ray-tracing to simulate the interaction of light with a simulated landscape and atmospheric models in an effort to generate realistic at-sensor radiance data [12]. Recent enhancements to DIRSIG enable the user to provide line-of-sight vectors for each detector and pointing information for the sensor as input, enabling a unique level of sophistication for sensor modeling [13,14]. When used in conjunction with its orbital model, DIRSIG is able to simulate image data that is both radiometrically and geometrically realistic.…”

Simulating ground-based measurements of spectral signatures of resident space objects

“…DIRSIG™ uses the Simplified General Perturbations Version 4 (SGP4) orbit model [17] to predict the satellite position during the period of observation. The SGP4 output is in the True Equator Mean Equinox (TEME) coordinate system that needs to be converted into Earth-Centered Earth-Fixed (ECEF) coordinates (also known as the geocentric coordinate system) supported by DIRSIG™ [17]. In this reference frame, the orientation of the satellite is defined to always look to the center of the Earth (ECEF origin).…”

An Analysis of the Side Slither On-Orbit Calibration Technique Using the DIRSIG Model

“…DIRSIG supports scenes developed from complex geometries or can use radiance data directly as input to describe the synthetic landscape. Recent enhancements to DIRSIG support the development of a sophisticated data-driven sensor model [12]. If the user is able to make lab measurements, DIRSIG accepts line-of-sight measurements to define the focal plane layout, platform jitter, and can handle inputs of gains, biases, relative spectral response functions, noise, etc.…”