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Proposing the PSO-based least squares algorithm for parameters estimation.Simultaneous properties measurement of multi-layered material.Analyzing the unpredictable effect from properties of multi-layered structure on the reflection spectrum.Improving the widely-used least squares inversion method by particle swarm optimization.Advanced multi-layered materials with superior performance are required for many applications. The non-destructive characterization of multi-layer properties is a hot spot of current research. The least squares inversion method using the reflection spectrum has been developed and widely used to estimate the properties of thin single layers simultaneously. However this method has the problems of a loss in speed and simplicity, and a local optimal solution, especially in the cases of a multi-layered structure because of the increasing estimated parameters and the uncertainty influence from the parameters. Particle swarm optimization (PSO) is a robust global search algorithm similar to ‘bird’ foraging, which can be used to improve the performance of the least squares inversion algorithm. This paper has proposed a PSO-based least squares estimation using the ultrasonic reflection spectrum to make simultaneous measurement. The simulation and experiment, carried out on the aluminum-TC4 bi-layered material, tested and proved the capability of the new algorithm. The real measured parameters and the estimated parameters were obtained. The results have been compared to analyze the errors of the estimated parameters.