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由于现有的基于最大比合并MRC(Maximum Ratio Combination)的联合搜索定位算法实现复杂度高,为降低其计算复杂度,提出基于网格搜索的加权最大似然代价函数定位算法WMLGS(Weighted ML Grid Search Localization)。仿真结果表明:MRC和WMLGS算法的定位性能近似相等,在无地球表面约束条件下均优于单独时差或频差定位性能,并且逼近克拉美罗联合界,同MRC相比,WMLGS节省了一半左右的计算量,因此更具有实用价值。
Due to the high complexity of the existing joint search and location algorithm based on Maximum Ratio Combination (MRC), in order to reduce its computational complexity, a WMLGS (Weighted ML Grid) algorithm based on grid search is proposed, Search Localization. The simulation results show that the positioning performance of MRC and WMLGS algorithms are approximately equal and are better than the separate time-difference or frequency-difference positioning performance without earth surface constraints, and approximate the Kelameluo joint community, compared with MRC, WMLGS save about half The amount of computation, so more practical value.