SciTec developed the Laser Threat Simulator to provide reliable, documented pointing for laser observables testing

SciTec has extensive experience in rapid prototyping, sensor architecture development, electronics miniaturization, and fieldable system production. SciTec also develops custom data collection systems with high volume data storage requirements and using small format computers. In addition, SciTec integrates signal processing capabilities into custom sensors, including preprocessing, dedicated algorithms implemented in FPGAs, and parallel computing architectures. System functionality is enhanced due to SciTec's field testing experience.

SciTec's electro-optic system designs incorporate turnkey operation into custom packages

In order to ensure that sensor systems meet customer requirements, SciTec employs a unique end-to-end design philosophy. The approach combines detailed models and/or existing data for the phenomenological (target signature and atmospheric propagation) conditions, system optical throughput, detector specifications, and electronic transfer function. The phenomenological inputs to the design often are leveraged by first principles physics-based signature models which are unique to SciTec. In addition, optical and electronic design parameters are generated using sensor models which have been repeatedly validated using custom laboratory prototypes. This design approach allows SciTec to produce systems with minimal redesign and high confidence of meeting specification.

Polygon scanner used for calibration of laser systems

SciTec's history of success in instrument design and in testing is largely the result of the philosophy that instrument calibration should be a fundamental component of any electro-optic sensor system. Instrumentation developed by SciTec often employs integrated witness sensors and built-in tests to ensure that subsequent measurements are both accurate and repeatable. In addition, calibration accuracy is considered in the design phase in order to provide estimates of uncertainty on the final data products which are critical to the data analyst.