【摘要】 面向未来低空通信与感知一体化系统，单基站感知面临多目标参数配对困难、感知精度不足、感知维度受限的问题。为此，考虑单个发送基站和多个接收基站构成的低空通感一体化系统，提出了多基站协同的三维坐标和三维速度联合六维感知方法。首先，进行空间平滑处理，消除多目标回波信号之间的相干性。其次，设计基于旋转不变技术信号参数估计（ESPRIT）的多目标方位角、俯仰角、距离以及径向速度联合估计算法，实现多目标参数自动配对，避免传统算法中复杂的参数配对操作。然后，分别利用各基站的角度和距离参数估计结果，提出多个低空目标三维空间坐标的单基站几何定位策略，并设计信噪比加权融合的多基站融合定位方法。最后，基于融合定位结果，构建多目标与多基站的相对角度映射模型，并利用各基站径向速度参数估计结果，获得多个目标真实三维速度的最小二乘解析解，实现低空多目标的六维感知。仿真表明，所提参数联合估计算法的根均方误差显著低于传统正交匹配追踪算法，并接近克拉美罗理论下界，所提方法实现了一维径向速度感知到三维真实速度感知的扩展。更多还原

【Abstract】 For future low-altitude integrated sensing and communication systems,monostatic sensing faces challenges such as multi-target parameter pairing difficulties,insufficient sensing accuracy,and limited sensing dimensions.To address these issues,this paper considers a low-altitude integrated sensing and communication system consisting of one transmitting base station and multiple receiving base stations,and a multistatic collaborative six-dimensional sensing method is proposed to jointly estimate the three-dimensional location coordinates and three-dimensional velocity of low-altitude targets.First,spatial smoothing is performed to eliminate the coherence among multi-target echo signals.Then,based on the estimation of signal parameters via rotational invariance techniques (ESPRIT),an algorithm is designed to jointly estimate and automatically pair the multi-targets’ azimuth,elevation,range,and radial velocity,avoiding the complex parameter matching required by traditional algorithms.Next,using the angle and range parameter estimates from each base station,a monostatic geometric localization strategy is designed to acquire the three-dimensional coordinates of multiple low-altitude targets,and a multistatic fusion localization method is further proposed based on the signal-to-noise-ratio weighted fusion.Finally,based on the fused localization results,a relative angle mapping model for multiple targets and multistatic stations is established,and the least-squares solution for the true three-dimensional velocities of multiple targets is obtained by using the radial velocity estimates from each base station,thereby achieving six-dimensional sensing of low-altitude multi-targets.Simulation results show that the root mean square error of the proposed joint parameter estimation algorithm is significantly lower than that of the traditional orthogonal matching pursuit algorithm and approaches the theoretical Cramér–Rao lower bound.Moreover,the proposed method successfully extends the sensing from one-dimensional radial velocity to true three-dimensional velocity.更多还原