卫星导航多干扰源直接定位方法

Direct Position Determination of Multiple Interference Sources for Satellite Navigation

摘要:

卫星导航信号到达地面时非常微弱，容易受到各种干扰，给用户带来一定的影响；针对此种情况，面向卫星导航系统多干扰源定位场景，传统两步定位算法受参数估计精度影响较大， DPD_MVDR算法虽然改进了MUSIC算法需要估计目标数这一缺点，但由于使用固定网格分辨率，定位精度与计算复杂度二者无法兼得；针对上述问题，提出一种改进DPD_MVDR的直接定位方法，在直接定位这一关键技术上运用自适应网格细化，其最大优势在于只对干扰源位置附近的网格实现多级细化，能很好地兼顾定位精度与计算复杂度，避免了传统穷举搜索带来的巨大计算复杂度。首先使用DPD_MVDR算法在粗网格下进行位置初始估计，然后在估计位置处进行迭代自适应网格细化，在降低计算复杂度的同时，提高定位精度。仿真表明，改进算法在100 m网格分辨率下计算复杂度明显降低且较DPD_MVDR算法定位精度得到明显提高；适用于对定位精度和定位实时性均有一定要求的场景。

Abstract:

The satellite navigation signal is very weak when it reaches the ground, and it is susceptible to various interference, which brings certain impact to the user; In view of this situation, for the multi-interference source positioning scenario of satellite navigation system, the traditional two-step positioning algorithm is greatly affected by the parameter estimation accuracy, and the minimum variance distortion response with direct position determination (DPD_MVDR) algorithm, although the multiple signal classification (MUSIC) positioning algorithm needs to estimate the number of targets, due to the use of fixed grid resolution, the positioning accuracy and computational complexity cannot be combined. To solve the above problems, an improved DPD_MVDR direct location method is proposed, and adaptive mesh refinement is used on the key technology of direct location. Its biggest advantage is that it can only achieve multi-level refinement of the grid near the interference source location, which can well balance the positioning accuracy and computational complexity, and avoid the huge computational complexity caused by traditional exhaustive search. Firstly, DPD_MVDR algorithm is used to perform initial location estimation under coarse mesh, and then iterative adaptive mesh refinement is carried out at the estimated location to reduce the computational complexity and improve the positioning accuracy. The simulation results show that the improved algorithm is less complex and more accurate than DPD_MVDR algorithm at 100 m grid resolution. It is suitable for the scenarios that have certain requirements for positioning accuracy and real-time positioning.