摘要：Global Navigation Satellite System (GNSS) is vulnerable to interferences and has other shortcomings such as unreliable signals in locations that are indoors, in urban canyons, and deep mines. Therefore, the pseudolite (pseudo-satellite) positioning technology, which has gained wide attention in recent years, is used to complement and enhance GNSS. The constellation layout of pseudolites creates geometrical benchmarks in spatial positioning, which in turn affects the receiver positioning accuracy by impacting the Dilution of Precision (DOP) value of each location point within the service area. The constellation layout of pseudolites poses a combinatorial optimization problem with multiple constraints, given the service area and station layout area, such as the distance between the pseudolite and the receiver, making the indicators of spatial configuration and redundancy maintenance and the availability within the service area to achieve best. An improved Adaptive Genetic Algorithm (AGA) is presented based on the mathematical modeling of pseudolite positioning and constraints. The simulation results show that the novel algorithm can effectively solve the optimization problem associated with the constellation layout of pseudolites under a variety of constraints.
