Radar sensors are used for space situational awareness (SSA) to determine collision risk and detect re-entry of space objects. The capability of SSA radar system includes radar sensitivity such as the detectable radar cross-section as a function of range and tracking capability to indicate tracking time and measurement errors. The time duration of the target staying in a range cell is short; therefore, the signal-to-noise ratio cannot be improved through the pulse integration method used in pulse-Doppler signal processing. In this study, a method of improving the signal-to-noise ratio during range migration is presented. The improved detection performance from signal processing gains realized in this study can be used as a basis for comprehensively designing an SSA radar system.

With increased human activity in space, the risk of re-entry and collision between space objects is constantly increasing. Hence, the need for space situational awareness (SSA) programs has been acknowledged by many experienced space agencies. Optical and radar sensors, which enable the surveillance and tracking of space objects, are the most important technical components of SSA systems. In particular, combinations of radar systems and optical sensor networks play an outstanding role in SSA programs. At present, Korea operates the optical wide field patrol network (OWL-Net), the only optical system for tracking space objects. However, due to their dependence on weather conditions and observation time, it is not reasonable to use optical systems alone for SSA initiatives, as they have limited operational availability. Therefore, the strategies for developing radar systems should be considered for an efficient SSA system using currently available technology. The purpose of this paper is to analyze the performance of a radar system in detecting and tracking space objects. With the radar system investigated, the minimum sensitivity is defined as detection of a 1-m2 radar cross section (RCS) at an altitude of 2,000 km, with operating frequencies in the L, S, C, X or Ku-band. The results of power budget analysis showed that the maximum detection range of 2,000 km, which includes the low earth orbit (LEO) environment, can be achieved with a transmission power of 900 kW, transmit and receive antenna gains of 40 dB and 43 dB, respectively, a pulse width of 2 ms, and a signal processing gain of 13.3 dB, at a frequency of 1.3 GHz. We defined the key parameters of the radar following a performance analysis of the system. This research can thus provide guidelines for the conceptual design of radar systems for national SSA initiatives.

The key risk analysis technologies for the re-entry of space objects into Earth’s atmosphere are divided into four categories: cataloguing and databases of the re-entry of space objects, lifetime and re-entry trajectory predictions, break-up models after re-entry and multiple debris distribution predictions, and ground impact probability models. In this study, we focused on reentry prediction, including orbital lifetime assessments, for space situational awareness systems. Re-entry predictions are very difficult and are affected by various sources of uncertainty. In particular, during uncontrolled re-entry, large spacecraft may break into several pieces of debris, and the surviving fragments can be a significant hazard for persons and properties on the ground. In recent years, specific methods and procedures have been developed to provide clear information for predicting and analyzing the re-entry of space objects and for ground-risk assessments. Representative tools include object reentry survival analysis tool (ORSAT) and debris assessment software (DAS) developed by National Aeronautics and Space Administration (NASA), spacecraft atmospheric re-entry and aerothermal break-up (SCARAB) and debris risk assessment and mitigation analysis (DRAMA) developed by European Space Agency (ESA), and semi-analytic tool for end of life analysis (STELA) developed by Centre National d’Etudes Spatiales (CNES). In this study, various surveys of existing re-entry space objects are reviewed, and an efficient re-entry prediction technique is suggested based on STELA, the life-cycle analysis tool for satellites, and DRAMA, a re-entry analysis tool. To verify the proposed method, the re-entry of the Tiangong-1 Space Lab, which is expected to re-enter Earth’s atmosphere shortly, was simulated. Eventually, these results will provide a basis for space situational awareness risk analyses of the re-entry of space objects.