Space Situational Awareness (SSA) by ground-based digital-array radar systems has been attracting global attention in recent years. One of its fundamental tasks is to provide accurate collision forecasting between space debris and active satellites, leading to increased avoidance probability. This is achieved by a rigorous signal processing stage that successfully detects stray space debris and accurately estimates its parameters from the radar data: range, direction-of-arrival, radial velocity, etc. The objective of this research is to improve the radar performance through the adaptation of the signal processing scheme to SSA. It presents the shortcomings of several key aspects of traditional signal processing and proposes new methods for improved target detection and parameter estimation, supported by numerical demonstrations of a real radar system. The above-mentioned techniques ultimately lead to superior estimation accuracy, higher resource efficiency, and robust detection capabilities, contributing to enhanced SSA. Based on this research, new estimation methods and operational modes can be explored in the context of a single station and radar networks, leading to a safer near-Earth space.weiterlesen