Signal Processing Environment For Analysis and Reduction (SPEAR).

摘要

A need for a high-fidelity sensor design simulation model to accurately predict the envelope of the system performance and to offset the escalating cost of the system development and testing are 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.