The current and emerging global space traffic has called for extensive and intelligent spacecraft management systems that will cater a controlled navigation of growing population of spacecraft under the dynamically changing space environment. However, achieving this autonomous adaptability comes with complex space domain awareness issues. Over the past years, the Australian government and industrial organizations have been dedicatedly involved in multiple projects to address these challenges. This work highlights some of the key contributions of the Australian Government’s round 9 cooperative research centre project (CRC-P) titled “A sensor network for integrated Space Traffic Management for Australia", which is a joint venture of industry and academic researchers in the space sector. The program consists of passive radio frequency (RF) network sites located in the Australian Capital Territory, New South Wales, South Australia and Western Australia which detect communication signals from satellites operating in VHF, UHF, S, X and Ku bands. The sites are installed with a combination of directional and omnidirectional antennas which help covering the entire horizon. The RF data is integrated with optical data obtained from the UNSW Canberra’s 36cm, 2-degree field of view ‘VIPER’ telescope to provide enhanced monitoring of spacecraft. The combined information is then used for the orbit determination of the observed satellites. The preliminary results have depicted a successful orbit determination. The growing number of spacecraft add increasing levels of complexity for automated tracking, identification and characterization, which become infeasible to be processed using traditional techniques. To address this high dimensional, complex and dynamic problem for our space network, machine learning algorithms and deep neural networks are envisioned to provide a sophisticated solution. Hence, the project aims to achieve a cost effective, less-computationally intensive and robust system for space situational awareness.