A Method for Resolving Range Ambiguity of High-Frame-Rate Signals Based on Radial Velocity Constraint

To address the problem of the high computational complexity and low accuracy in traditional majority rule algorithm under high-frame-rate signal conditions, this paper proposes a radial velocity-constrained particle optimization method for resolving range ambiguity. First, by modifying the objective function of the positioning model, the dimension of the unknown parameters was reduced. Second, the particle swarm optimization algorithm was used to search for the optimal position of the objective function within a predetermined range, improving the stability and computational efficiency of resolving range ambiguity. Finally, by integrating an unambiguous radial velocity constraint, the algorithm confines the target location, thereby mitigating the problem of cycle skipping arising from insufficient constraints in algorithms that resolve range ambiguity using only delay information. This enhancement significantly diminishes the likelihood of converging to local optima in the solution space. Simulation results show that the proposed method significantly enhances the performance and stability in terms of resolving range ambiguity.