Metallic mesh coatings are used on visible and infrared windows and domes widely to provide shielding from EMI (Electromagnetic Interference). In this paper, different EMI mesh geometries are compared with each other regarding various performance parameters. But to decide the best fitting EMI mesh geometry to particular optic system is a little bit complicated issue. Therefore, we try to find a simple optimization methodology to decide best EMI mesh geometry design that fits our particular high performance ISR (Intelligence, Surveillance and Reconnaissance) systems.
The choice of the Field of View (FOV) of imaging sensors used in airborne targeting applications has major impact on the overall performance of the system. Conducting a market survey from published data on sensors used in stabilized airborne targeting systems shows a trend of ever narrowing FOVs housed in smaller and lighter volumes. This approach promotes the ever increasing geometric resolution provided by narrower FOVs, while it seemingly ignores the influences the FOV selection has on the sensor’s sensitivity, the effects of diffraction, the influences of sight line jitter and collectively the overall system performance. This paper presents a trade-off methodology to select the optimal FOV for an imaging sensor that is limited in aperture diameter by mechanical constraints (such as space/volume available and window size) by balancing the influences FOV has on sensitivity and resolution and thereby optimizing the system’s performance. The methodology may be applied to staring array based imaging sensors across all wavebands from visible/day cameras through to long wave infrared thermal imagers. Some examples of sensor analysis applying the trade-off methodology are given that highlights the performance advantages that can be gained by maximizing the aperture diameters and choosing the optimal FOV for an imaging sensor used in airborne targeting applications.