A Bistatic Sensing System in Space-Air-Ground Integrated Networks

Sensing is anticipated to have wider extensions in communication systems with the boom of non-terrestrial networks (NTNs) during the past years. In this paper, we study a bistatic sensing system by maximizing the signal-to-interference-plus-noise ration (SINR) from the target aircraft in the space-air-ground integrated network (SAGIN). We formulate a joint optimization problem for the transmit beamforming of lowearth orbit (LEO) satellite and the receive filtering of ground base station. To tackle this problem, we decompose the original problem into two sub-problems and use the alternating optimization to solve them iteratively. Using techniques of fractional programming and generalized Rayleigh quotient, the closed-form solution for each sub-problem is returned. Simulation results show that the proposed algorithm has good convergence performance. Moreover, the optimization of receive filtering dominates the optimality, especially when the satellite altitude becomes higher, which provides valuable network design insights.

I. Introduction

Sensing has been envisioned to become a key technology in the fifth generation (5G) and beyond wireless communication systems for obtaining emerging applications such as navigation and monitoring [1]. By applying sensing techniques, the quality of service (QoS) in terms of mutual communications as well as continuous detection and tracking of targets can be enhanced [2]. Due to the expansion of global networks and the advancement of air communication and transportation, vital significance has been brought to the task of sensing aircraft for aviation safety, traffic efficiency, and aerial security purposes [3]. By tracking and monitoring the movements of aircraft, not only the airspace traffic can be better controlled, but potential threats or unauthorized airspace entries can be detected promptly as well. Therefore, the enhancement of sensing quality for aircraft remains as a crucial problem.