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 low-earth 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.

翻译：随着近年来非地面网络（NTN）的蓬勃发展，感知技术在通信系统中预计将获得更广泛的应用。本文研究了一种空天地一体化网络（SAGIN）中通过最大化来自目标飞机的信号与干扰加噪声比（SINR）的双基地感知系统。我们针对低地球轨道（LEO）卫星的发射波束成形和地面基站的接收滤波，构建了一个联合优化问题。为解决该问题，我们将原问题分解为两个子问题，并采用交替优化方法进行迭代求解。通过分式规划和广义瑞利商技术，我们得到了每个子问题的闭式解。仿真结果表明，所提算法具有良好的收敛性能。此外，接收滤波的优化对系统最优性起主导作用，尤其在卫星高度增加时更为显著，这为网络设计提供了有价值的参考依据。