Convex relaxation methods are commonly used to solve nonconvex mathematical optimization problems. These methods transform the original nonconvex problem in such a way that effective methods of solving convex optimization problems become applicable. Thus, a convex problem giving the approximate solution of the original task can be solved instead of the original computationally complex problem. Presented is the application of semidefinite relaxation to the task of determining the optimal set of Global navigation satellite systems signals that are selected for processing while solving the positioning problem. The need for signals set optimization is due to large number of navigation satellites accessible for the customers on the ground level. This binary optimization problem is hard to solve in real time. Two approaches are proposed to reduce the initial problem to the convex problem allowing the effective solution.

凸松弛方法通常用于解决非凸数学优化问题。这些方法以解决凸优化问题的有效方法变得适用的方式转换了原始的非凸问题。因此，可以解决给出原始任务的近似解的凸问题，而不是原始的计算复杂的问题。本文介绍了半确定松弛在确定最佳全球导航卫星系统信号集的任务中的应用，这些信号是在解决定位问题时选择进行处理的。信号集优化的需要是由于地面上的客户可以使用大量导航卫星。这种二进制优化问题很难实时解决。