Faster with CLEAN - An exploration of the effects of applying a nonlinear deconvolution method to a novel radiation mapper

摘要

This paper examines the suitability and potential of reducing the acquisition requirements of a novel radiation mapper through the application of the non-linear deconvolution technique, CLEAN. The radiation mapper generates a threshold image of the target scene, at a user defined distance, using a single pixel detector manually scanned across the scene . This paper provides a discussion of the factors involved and merits of incorporating CLEAN into the system. In this paper we describe the modifications to the system for the generation of an intensity map and the relationship between resolution and acquisition time for a target scene. The factors influencing image fidelity for a scene are identified and discussed with the impact on fill-factor of the intensity image, which in turn determines the ability of the operator to accurately identify features of the radiation source within a target scene. The CLEAN algorithm and its variants have been extensively developed by the radio astronomy community to improve the image fidelity of data collected by sparse interferometric arrays. However, the algorithm has demonstrated surprising adaptability including terrestrial imagery, as detailed in Taylor et al. SPIE 9078-19 and Bose et al., IEEE 2002. CLEAN can be applied directly to raw data via a bespoke algorithm. However, this investigation is a proof-of-concept and thus requires a well tested verification method. We have opted to use the public ally available implementation of CLEAN found in the Common Astronomy Software Applications (CASA) package. The use of CASA for this purpose dictates the use of simulated input data and radio astronomy standard parameters. Finally, this paper presents the results of applying CLEAN to our simulated target scene, with a discussion of the potential merits a bespoke implementation would yield.