摘要：

在低轨单星测频定位中，网格搜索算法在高精度搜索时运算量大，且泰勒展开迭代方法存在定位不收敛的问题。为此，提出一种基于网格搜索与泰勒展开迭代相结合的定位方法。利用网格搜索算法实现粗定位，将该定位结果作为初始值代入泰勒迭代算法，从而对目标进行高精度定位。推导地球表面约束条件下低轨单星测频定位精度的克拉美劳下界，分析各种因素对定位精度的影响，仿真结果表明，在星下点两侧附近区域，低轨单星测频定位方法能够有效地实现对目标的定位。

关键词: 低轨卫星, 多普勒频移, 无源定位, 误差分析, 定位精度, 克拉美劳下界

Abstract:

In the single Low Earth Orbit(LEO) satellite localization system, grid search algorithm requires large amount of computation in the precision of search and Taylor-series linearization algorithm exists localization convergence problem. In view of this, a new method is proposed which is combined of grid search and Taylor-series linearization algorithm. Using grid search method to achieve the rough location and taking the location result as the initial value of the Taylor-series linearization, the high-precision position of target can be got. The constrained Cramer-Rao Lower Bound(CRLB) for the source localization estimation is derived with the constraints of altitude. Simulation results are provided to analyze the effects of various factors on the location precision. The analysis results show that the localization from frequency measurement by the single LEO satellite can effectively achieve the target location on both sides below the satellite.

Key words: Low Earth Orbit(LEO) satellite, Doppler-shift frequency, passive localization, error analysis, location precision, Cramer-Rao Lower Bound(CRLB)

中图分类号: 

• TN971