Target detection presents many challenges for military sensor imaging system where there is a strong dependency on the camera resolution. From a performance analysis perspective, the target image is typically considered to be either a fully resolved object or else an unresolved point source. However, in many longer-range detection systems, the size of the target’s image on the focal plane lies between these two states and often transitions between them during an engagement. Furthermore, the position of the target’s image relative to the centre point of a pixel will vary with time, and this produces a fluctuation in the measured target signature that affects the peak Signal to Noise Ratio (SNR). The modelling and simulation of an imaging sensor’s performance associated with the target image sampling by a focal plane array is discussed in terms of three critical factors: geometric resolution, optical blur, and image position on the focal plane. Image sampling factors are introduced to provide a correction to the SNR and the associated detection range equation. In many imaging applications, target detection is limited by scene clutter whose spatial characteristics vary with range. Different approaches for modelling the clutter in the target detection process are considered and the effect of image sampling on the system performance is discussed. A traditional approach for introducing clutter into the calculation of detection range is the use of a Clutter Equivalent Irradiance (CEI) term. In this paper, a correction to the CEI is introduced which compensates for clutter spatial correlation and the effects of sensor processing.
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