The Faculty of Mathematics, Physics and Informatics of Comenius University in Bratislava, Slovakia (FMPI CU) operates its own Astronomical and Geophysical Observatory in Modra, Slovakia (AGO). AGO consists of several optical systems, from which some were developed by FMPI. One of the mentioned systems is a 70-cm Newton telescope (AGO70) with primary focus on the space debris research, space surveillance and tracking (SST) to support the European attempts for autonomous SST operations.

AGO70 has several parallel scientific programs with primary focus on space debris characterization. In the last two years we created our own space debris light curve catalogue which is available for scientific community. The light curve catalogue is further used for the BVRI photometry where the shape of the phase-diagram and the synodic rotation period define the strategy for the data acquisition and processing once acquired with multi-band filters. Astrometric measurements are used for three goals. To validate and calibrate the AGO70 system’s data, to support the cataloguing efforts which requires orbit determination and improvement, and to improve the tracking efficiency of Satellite Laser Ranging stations.

Part of the improvement of AGO70 system is also hardware and software modifications. There have been efforts given to the improvement of the image processing software responsible for the real-time processing of acquired FITS frames. This so-called Image Processing Elements (IPE) pipeline is based on the modular design to make it more flexible for modifications and implementation to other systems. Currently, there are nine IPEs in total responsible for many different tasks like image segmentation, astrometric reduction, tracklet building or object correlation.

In our work we will present the AGO70 system’s technical characteristics and observation programs. We will introduce the overall design of the system and its functionalities. The planning, acquisition and processing of light curves, BVRI photometric data, and astrometric measurements will be discussed in detail. We will present the image processing pipeline which improves the obtained data’s quality and latency.