As complex battlefield environment requires rapid and accurate positioning of sky-wave radar, a positioning model based on multi-strategy improved sparrow search algorithm is proposed. First, cubic chaotic mapping, dynamic adjustment of step factor, reverse learning, and mixed mutation operator are used to invent an improved sparrow search algorithm. Then, the improved sparrow search algorithm is used to find the best-fit kernel function parameters and weight coefficient of mixed kernel of hybrid kernel extreme learning machine (HKELM). Finally, the optimized HKELM is used to locate the target detected by the skywave radar. The results show that the accuracy and stability of improved sparrow search algorithm are not only superior to the HKELM location model which is optimized by the basic sparrow search algorithm, but also stronger than the extreme learning machine (ELM) location model. In other words, the effectiveness of the method is proved.