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NOAA plans to build a Geostationary Lightning Mapper (GLM) whose objectives are providing continuous, full-disk lightning measurements for storm warning and science applications. Due to limited telemetry bandwidth, much of the detection processing will be done autonomously.Since the contractor is responsible for the autonomously generated output, which is detection reports -not images, we took a design approach that did not stop with a signal to noise calculation but instead simultaneously considers the effects of hardware configurations and algorithm choices. Key requirements for GLM are the probability of detection (P D ) and probability of false alarm (P FA ). Our approach allows us to provide a system with the best P D and P FA performance and the best value. We have accomplished this by developing an analytical model that can find "knees-inthe curve" in our hardware configuration selections and an algorithm prototype that provides realistic end-to-end performance. These tools allow us to develop an optimal system since we have a good handle on realistic performance prior to launch.Our tools rely on descriptions of lightning phenomena embodied in probability densities we developed for the amplitude, temporal and spatial distribution of lightning optical pulses. The "analytic model" uses tabulated integration formulae and conventional numerical integration to implement an analytical solution for the P D estimate. The average P D is quickly computed, making the analytic model the choice for rapid evaluation of sensor design parameter effects.The "algorithm prototype" utilizes simulation, consisting of data cubes of time elapsed imagery containing lightning pulses and structured backgrounds, and prototyped detection and false alarm mitigation algorithms to estimate P D and P FA . This approach provides realistic performance by accounting for scene spatial structure and apparent motion.We discuss the design and function of these tools and show results indicating the variation of P D and P FA performance with changes in sensor and algorithm parameters and how we use these tools to improve our instrument design capabilities.

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An integrated optics. controls. and structures modeling tool has been developed to analyze the perfonmince of complex electro-optical (EO) sensing systems. Hosted within an object-oriented graphical environment (Khoros) developed by the University of New Mexico. complex systems such as active ground-based telescopes. airborne spectrometers. and spacebased sparse array telescopes can be simulated and rapidly evaluated. The TAOS model integrates data products from existing codes such as MATLAB. CODE 5. NASTRAN, and others to allow multi-disciplinary parametric analysis of system performance. Because the model includes accurate physical optics and radiometric representations. almost any function of an optics system can be quickly generated and studied. In addition, degrading effects of dynamic structures, use of compensating control systems, and effects of the observing environment (wind load. boundary layer. and seeing) can also be included. Use of this simulation tool on NASA programs such as the Space Telescope Imaging Spectrometer has reduced design schedules by factors of three. Other typical analysis applications include the study of atmospheric compensated imagmg systems usmg combined adaptive optics/post-processing techniques, simulation of hyper-spectral imagers. and methods for achieving coherent phasing of telescope arrays. This paper also provides a progress report on TAOS modeling of the European Southern Observatoiy (ESO) Very Large Telescope (VLT). SPIE Vol. 2217/271 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/22/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx