一种基于粒子群优化的卫星仅测频被动定轨新算法

提出一种新的卫星对卫星仅测频被动定轨算法,采用粒子群优化算法(PSO)解决多维全局优化问题。首先,建立了卫星对卫星仅测频被动定轨的数学模型;其次,基于粒子群优化算法提出了对目标卫星轨道根数的估计方法;再次,推导了参数估计误差的克拉-美劳(CRLB)下限。最后通过计算机仿真对算法的性能进行了验证。多次仿真结果表明:该算法的参数估计误差接近克拉-美劳下限,且算法的运算量明显优于网格搜索法。

A New Satellite Passive Locating Algorithm Using Frequency-only Measurements Based on PSO

A new satellite to satellite passive locating algorithm using Frequency-Only measurements is proposed based on Particle Swarm Optimization (PSO). Firstly, the mathematic model of satellite to satellite passive locating is established. Secondly,the estimation method of the target satellite's orbital elements is proposed based on PSO. Thirdly, the corresponding Cramer-Rao lower bounds (CRLB) are then deduced. Finally, performance is validated through computer simulations. Simulations indicate that the proposed method is effective in terms of the estimation quality compared with CRLB and superior in computation burden to the grid search method.