  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.
