Compressive sensing applications for single detector seekers

Abstract

In this work, the application of compressive sensing theory to single detector seekers is investigated. Compressive sensing is a novel signal processing technique which shows that a compressible signal can 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. Single detector infrared seekers suffer from low performance compared to infrared seekers utilizing 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. 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 other sampling methods proposed in the literature.