SVOM/VT: Real-Time Onboard Data Processing

TL;DR

The paper presents the design and implementation of a real-time onboard data processing pipeline for the SVOM Visible Telescope, enabling rapid identification of GRB optical counterparts within strict bandwidth constraints.

Contribution

It introduces a novel FPGA-CPU based software architecture and algorithms for real-time image processing and data compression onboard the telescope.

Findings

78% of promptly slewed SVOM GRBs had available VHF data.

56% of these led to optical counterpart identification.

Optical counterparts were typically identified within 18 minutes.

Abstract

The SVOM Visible Telescope (VT) is critical for the rapid identification of gamma-ray burst (GRB) optical counterparts, particularly for high-redshift candidates that require immediate infrared spectroscopic follow-up. To address the stringent bandwidth constraints of the VHF downlink while ensuring real-time data availability, we developed the VT Onboard Data Processing Pipeline (VOPP).This paper details the software architecture, algorithms, and hardware implementation of VOPP using an FPGA and a CPU. The pipeline performs essential real-time tasks, including image quality assessment, dark and flat-field correction, and optimized image stacking to mitigate cosmic ray contamination and variable background noise. Furthermore, it generates compact source catalogs and highly compressed 1-bit images to facilitate rapid downlink.In-flight performance analysis confirms the pipeline's robustness, demonstrating the availability of VT VHF data for 78 percent of promptly slewed SVOM GRBs, with 56 percent leading to the identification of optical counterparts, typically within 18 minutes post-trigger.