Signal Detection and Parameter Estimation of Fence-type Space Surveillance Radar

Responding to the severe threat to the space activities from increasing LEO space debris, orbital object surveillance and cataloguing based on ground-based radar has aroused much attention from the world. However, the success of the space debris surveillance system strongly depends on the performance of signal detection and parameter estimation of the radar system. This paper presents a novel method for space debris detection and motion parameter estimation based on the famous fence-type space surveillance radar system. Based on the observation that orbital debris are sparsely distributed in the observed fence, we formulate this problem as a sparse signal reconstruction problem with respect to an overcomplete dictionary, defined using three motion parameters. Our simulation results show that the proposed method provides high detection and estimation performance, is robust to low Signal-to-Noise Ratio (SNR), and exhibits super-resolution properties.