Improved Analysis Techniques for Characterizing Jitter in Beam Control Systems (Phase 2)

Industry: SBIR

Applications: Research and Development

The US Air Force needs a system to help identifying root-causes of jitter in HEL beam alignment systems. This is of particular interest to the USAF as jitter smears the HEL beam on target, reducing its integrated intensity and therefore its target damage capability. Jitter is caused by several disturbances introduced in the beam alignment system with multiple sources and complex interactions between the multitude of sub-systems and components. With the current state-of-the art it is not possible to unequivocally identify sources of jitter from the analysis of the jitter signal alone. Rather, a comprehensive, yet streamlined and efficient, test plan to map the relevant sub-systems/components is required. A process has been established using strategic measurement techniques and advanced signal processing algorithms to quantify the jitter sources and paths in a consistent and accurate manner. This process was further developed by testing on a variety of different HEL beam control installations to ensure the algorithms were optimized to effectively address jitter in all applications. The algorithms and test process will then be developed into a “Jitter Vibration Decomposition Toolbox” software program to allow increased efficiency for testing personnel to perform jitter analysis. BENEFIT: The primary objective of this Phase II project was to deliver to the USAF test and signal analysis tools to decompose beam jitter into its most important contributions. The immediate benefit was for time and cost savings during the integration phase of an HEL system when much of the jitter root-cause investigation should take place. The improvement in testing efficiency and more applicable output will lead to the supplier base implementing updated test procedures to impact their design process with updated models and more informed design decisions. This need for better and more efficient testing methods is not unique and the automated signal processing toolbox developed in this Phase II project will be the core for developing similar toolboxes geared towards other industries such as automotive, consumer products and off-highway.

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