Image generation for single detector infrared seekers via compressive sensing

In this paper, we investigate the application of compressive sensing theory to single detector infrared seekers. Compressive sensing is a novel signal processing technique which enables a compressible signal to be constructed using fewer measurements obtained in a specific way below the Nyquist rate. Single detector image reconstruction applications using compressive sensing have been shown to be successful. Infrared seekers utilizing single detectors suffer from low performance compared to costly focal plane array detectors. The single detector, pseudo-imaging rosette scanning seekers scan the scene with a specific pattern and process the resultant signal with signal processing methods to estimate the target location without forming an image. In this context, this type of old generation seekers can be converted to imaging systems by utilizing the samples obtained by the scanning pattern in conjunction with the compressive sensing theory framework. In this study, infrared images have been reconstructed from samples obtained by the rosette scanning pattern for different sample numbers and it has been shown that the results obtained are comparable to the results obtained by other sampling methods proposed in the literature.