Investigations on Systems and Methods for Performance Simulation and Characterization of Spaceborne Electro-optical Imaging Systems

Abstract

The science of remote sensing from spaceborne platforms has significantly evolved owing to technological advancements in Electro-optical (EO) imaging systems. Indian Space Research Organisation (ISRO) has spearheaded design and development of spaceborne EO imaging systems in India for a host of civilian applications, such as, Earth-resource management, ocean monitoring, disaster management, agriculture management, large-scale mapping, cartography, weather forecasting, etc. Some technologically advance remote sensing missions under ISRO0 s flagship “Indian Remote Sensing (IRS)” programs are; IRS-1C/1D, Resourcesat-1 and 2 payloads, Ocean Color Monitor (OCM-1 and 2), a series of high-resolution cartographic cameras and so on. These missions have provided sustainable services to the user community. A continuous demand from the country for multipurpose remote sensing missions calls for the development of various kinds of state-of-the-art EO imaging systems and related technologies. A spaceborne EO imaging system operates in panchromatic, multi-spectral or hyper-spectral bands spanning over visible and near infrared (VNIR) part of electromagnetic (EM) spectrum to provide application-specific spatial resolution and swath coverage. Typically, an EO imaging systems comprise an optical telescope (reflective, refractive or catadioptric), light-sensing solid-state device (e.g. Charge-Coupled Devices (CCD), Time Delay and Integration (TDI) detectors, etc.), mechanical structures to accommodate optical and detector components, detector drive and processing electronics, low-noise power supplies, and spacecraft mainframe elements. All these subsystems are integrated, performance optimized and tested under space environmental conditions before launch. Extensive pre-flight characterization helps demonstrate performance compliance, identify deficiencies to aid in optimization process and provide assessment on achievable in-orbit performance. Subsequently, after the x xi launch, in-orbit performance consistency is evaluated to ensure reliable mission outcomes. Design, development, testing, characterization and in-orbit operations of EO imaging systems involve complex multidisciplinary processes. Achieving desired EO performance to meet user expectations requires development of robust and efficient systems and methods for performance estimation and characterization during the entire life-cycle of the imaging system. This study is an attempt to understand the complex interaction of imaging system elements and develop required systems and methods for EO performance simulation and characterization to aid in the design and development of IRS imaging systems. The first part of this thesis describes various aspects related to the development of EO performance modeling and simulation tool. First, a comprehensive physics-based model for IRS imaging systems has been developed. The model accounts for all the elements in the image transformation process that determine the radiometric and geometric fidelity of the image. This includes, target surface reflectance characteristics, atomospheric effects, imaging geometry, optical system behavior, spectral response, detector characteristics, mechanical elements and electronics system effects, Assembly, Integration and Testing (AIT) errors, etc. Based on this physics-based model, an EO performance simulation tool has been developed. The tool has three basic modules: scene simulation module, sensor simulation module and performance visualization module. The scene module generates top-of-atmosphere (TOA) radiance scene for any synthetic targets in both laboratory and in-orbit imaging conditions. For in-orbit imaging condition, the proposed simulation tool integrates the 6SV1 code Vermote et al. (1997) in the simulation environment using a python interface, known as Py6S Wilson (2013). This enables generation of TOA radiance map based on various scene-sensor geometry and atmospheric conditions. The sensor simulation module uses comprehensive radiometric and geometric models developed for IRS imaging systems at higher abstraction level. The sensor module provides a digital count map (image) of selected input scene by applying various sensor effects. The visualization module enables qualitative and quantitative evaluation of EO imaging system performance in terms of image display, Signal-to-noise ratio (SNR), Photon Transfer Curve (PTC) based Camera Gain (CG), Modulation Transfer Function (MTF), Square-Wave-Response (SWR) and National Image Interpretability Rating Scale (NIIRS). The tool enables sensitivity studies for any imaging system in terms of NIIRS rating scale. A simple, yet effective Graphical User Interface (GUI) is developed based on LabVIEWTM platform for easy navigation through various scene, sensor and visualization modules. The simulation tool is extensively validated by predicting the EO performance of the Resourcesat-2 LISS-4 imaging system. The efficacy of the simulation tool is demonstrated by studying the sensitivity of NIIRS levels to AIT errors of the proposed high-resolution camera. The second part of this thesis deals with the development of various robust and efficient systems and methods for radiometric and geometric performance characterization of IRS imaging systems during the development and in-orbit operational phase. In this direction, first, a quantitative analytical framework for PTC characterization of IRS imaging system has been developed. The framework not only enables comparative studies among various signal chains to identify sub-optimally performing chains but also provides performance traceability from detector component level to the integrated imaging system level. Based on the developed framework, PTC characteristics of the Resourcesat-2 LISS-4 imaging system has been studied. Further, PTC characterization using a non-uniform source has been demonstrated, which is a simple, yet efficient substitute to the elaborate light characterization setup. This approach helps to provide performance traceability throughout the development and in-orbit operational phase. Spatio-temporal noise is one of the major sources of image degradations. In this xiii study, an analytical method is developed for spatio-temporal noise characterization of spaceborne imaging systems so as to identify potential noise sources present in the imaging system. Such a study will be quite helpful in implementing various noise reduction approaches in the imaging system. The method has been validated using laboratory test data of the Resourcesat-2 LISS-4 imaging system. High resolution spaceborne imaging systems are increasingly using TDI detectors in their focal planes owing to their higher sensitivity performance. However, errors in misalignment of TDI sensors in the focal plane can lead to MTF degradation due to smear. This study presents an efficient method for active alignment of multiple TDI detectors in the focal plane by intuitively operating them in the staring mode. The proposed method enables sub-pixel level alignment of multiple TDI detectors. Moreover, the developed method is useful for square-wave-response (SWR) measurements at integrated imaging system level. Finally, in this study, an image-based method has been developed to quantitatively determine the extent of misalignment among multiple TDI detectors in the focal plane during in-orbit operational phase. The method utilizes Canny edge operator and Hough transform to detect long edges in the images acquired in the detector overlap region. Change in slope of the edge in both the images helps determine misalignment between the detectors. Overall, this research work has led to the development of systems and methods for performance simulation and characterization of IRS imaging systems to significantly aid in EO imaging system realization process by supplementing and complementing the existing approaches.