LEO/MEO-Based Multi-static Passive Radar Detection Performance Analysis Using Stochastic Geometry

Recent developments in the launching of low-earth orbit (LEO) mega-constellations of communication satellites and medium-earth orbit (MEO) constellations of navigation satellites present an opportunity for target detection by passive radar receivers. System-level studies of multi-static passive radar detection performance of land and sea targets must account for diversity in the number and spatial distribution of the satellite transmitters. In this work, we model the distribution of satellite transmitters as a homogeneous Poisson point process and subsequently use stochastic geometry tools to derive the probability that a target is detected by at least one of the bistatic radar links between a satellite transmitter and a passive radar receiver. The proposed theoretical framework enables us to draw system-level performance insights into both LEO and MEO-based passive radar detection performance at a fraction of the computational costs (time and memory) of large-scale Monte Carlo simulations. Our study shows that LEO-based passive radar systems are likely to outperform MEO-based passive radar systems with comparable receiver characteristics due to their greater density and proximity to earth.