Enhanced Resolution for Closely-Spaced Objects From Optical Sensor Using FPA Offset

The problem of measurement extraction for two point targets in the focal plane array (FPA) of an optical sensor has been investigated in (Finelli et al., 2021) and (Lu et al., 2019). However, when the separation between the two targets is too small, they become unresolved-they yield a single unresolved merged measurement. This article presents an effective way to enhance the resolution for two such closely-spaced objects. One frame has the original image of the two targets, while a second frame has the FPA slightly shifted by a fraction of a pixel (called offset frame). The measurement extraction consists of two parts: estimation and detection. First, the targets' positions and intensities are jointly estimated based on the two frames' measurements (the original frame and the offset frame) under the resolved and unresolved target assumptions. The Cramer-Rao lower bound evaluates the estimation accuracy. Second, a hypothesis test is used to decide whether the two targets can be resolved or are unresolved. The generalized likelihood ratio test is used to perform decision making. Simulations investigate the effect of offset types, target separation, and signal-to-noise ratio on the measurement extraction and resolution. It is shown that adding offset to the image can provide more information about the closely-spaced objects, and offset enhances the resolution probability when compared to the two frames without offset.

Automated summary

This article presents an effective method to enhance the resolution for two closely-spaced targets. By jointly estimating the positions and intensities of the targets based on the original frame and the offset frame, it determines whether the targets can be resolved or not using a hypothesis test. Simulations show that adding offset to the image provides more information and enhances the resolution probability compared to frames without offset.