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The need for a high-fidelity sensor design simulation model to accurately predict the system performance envelope and to offset the escalating cost of the system development and testing is widely accepted by the defense community. This paper presents one such example of the modeling capability developed for the ballistic missile defense (BMD) application, called the signal processing environment for analysis and reduction (SPEAR) simulation. SPEAR has become a key IR sensor design and signal processing performance verification tool for the BMD Advanced Sensor Technology Program (ASTP), the Discriminating Interceptor Technology Program (DITP), and the ground based interceptor (GBI) and, where it is used for sensitivity analyses, algorithm evaluations, and performance assessments. For these programs, SPEAR provides an algorithm testing simulation to evaluate candidate signal processing options, and implement and test performance of algorithms proposed through advanced technology programs. In addition, SPEAR is used to process real world data to provide assessments of sensor performance and provide preflight predictions. The simulation has been interfaced to the synthetic scene generation model (SSGM), a community standard background and target scene generation simulation. Through this interface sensor performance can be evaluated against realistically modeled backgrounds to evaluate filtering, detection, and false alarm performance. SPEAR is a hi-fidelity passive infrared (IR) sensor and signal processing simulation for staring scanning, and hybrid sensors. It allows the user to specify the IR sensor physics including the sensor, optics, focal plane array or scan chip assembly, analog signal processor, time dependent and object dependent processing parameters and specific noise sources such as optics, jitter, fixed pattern noise, dark current, and gamma spike noise. SPEAR is an Ada/PVWAVE combination. The sensor and signal processing is written in Ada and the execution, parameter input, and function analysis are controlled with the graphical user interface (GUI) written in PVWAVE. The signal processing techniques available as options include time dependent processing techniques such as adaptive threshold detection, background estimation and removal, morphological filtering, match filtering, target signature extraction, and object dependent processing techniques such as centroiding and pulse matching. SPEAR has simulation control options to allow the user to execute and examine data per frame (mission mode) or in a statistical mode to investigate parametric sensitivities of the sensor performance. Documentation of SPEAR includes manuals on the GUI, the SPEAR application components, and guidelines for adding new algorithms and features. This paper provides a summary of key algorithm and options in SPEAR. Examples of performance analysis results are provided. The paper includes stochastic analyses of both the above- the-horizon and below-the-horizon engagements of target and background generated scenes using SSGM. Also discussed are the evaluation of radiometric measurement precision, angular measurement precision, and detection of targets of varying intensities with respect to varying sensor signal processing techniques.
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