The SVOM/ECLAIRs image trigger with wavelet-based background correction optimised with a one-year simulation of observations

CEA Paris-Saclay/IRFU, 91191 Gif-sur-Yvette, France
e-mail: nicolas.dagoneau@cea.fr

Received: 28 July 2021
Accepted: 24 June 2022

Abstract

Context. The Space-based multi-band astronomical Variable Objects Monitor (SVOM) mission under development will carry four instruments, and in particular the coded-mask telescope named ECLAIRs, with a large field of view of about 2 sr, operating in the 4–150 keV energy band. The trigger software on board ECLAIRs will search for high-energy transients such as gamma-ray bursts and peculiar behaviour (e.g. strong outbursts) from known X-ray sources, in order to repoint the satellite to perform follow-up observations with the onboard narrow field of view instruments.

Aims. The image trigger, one of the two algorithms implemented in the software on board ECLAIRs, produces images over periods of exposure ranging from 20 s to 20 min during which the Earth can cross the field of view. The Cosmic X-ray Background and contributions from known X-ray sources are expected to dominate the ECLAIRs astrophysical and instrumental background and must be taken into account and corrected prior to coded-mask image deconvolution in order to optimise the sensitivity to faint transients.

Methods. To correct these background components, we implemented and studied a traditional fitting method and a new method based on wavelet decomposition of the detector image. In order to study and to assess the performance of these methods, we performed a 1-yr simulation of the image trigger on board ECLAIRs. From the images produced during this realistic observation scenario of the SVOM mission, we also defined a way to analyse the sky images to search for new sources.

Results. We present the algorithms behind the image trigger on board SVOM/ECLAIRs. We show that the wavelet method we implemented provides similar results in terms of cleaning performance compared to the traditional fitting method, and has the benefit of not requiring any assumption on the shape of the background on the detector. We also calibrate the detection threshold to be adaptive and based on the quality of the reconstructed sky image.