In the complex environment of a shipbuilding base, the positioning algorithm based on RSSI ranging has large positioning errors and high computational time. This paper proposes an improved positioning algorithm based on the Salp Swarm Algorithm (SSA). The Tent chaotic mapping is employed for the purposes of initializing the population and maintaining the diversity of the population. This is to provide an update on the Levy flight strategy to the leaders position. The strategy employs elite guidance and Cauchy mutation, which are used by followers to address the shortcomings of the SSA, which is prone to local optima. The simulation results demonstrate that the positioning algorithm proposed in this paper enhances the positioning accuracy by approximately 79.87%, 28.88%, and 18.88% in comparison to the ISO, SSA, and LGSSA algorithms, respectively. This algorithm is capable of fulfilling the positioning requirements for the scheduling and maintenance of large mechanical equipment in shipbuilding bases.