Clustering sparse fitting scheme for GNSS multipath channel simulation

A GNSS multipath channel sparse fitting scheme based on K-medoids clustering was proposed to tackle the problem of a large amount of simulation computation and hardware resource overhead for GNSS channels, which is inconvenient for real-time performance evaluation and practical engineering applications. The equivalent reduced CIR (channel impulse response) parameters were extracted using a sparse fitting method based on K-medoids clustering CIR parameters extraction, and the channel simulation was realized using a sparse tapped-delay-line structure. The proposed method sparsely fits the original GNSS multipath channel model under the constraint of retaining multipath error by employing tapped-delay-line structure filter with fewer taps, which can decrease the complexity of simulation without requiring huge hardware resources. Simulation results show that the proposed scheme is effective by sparse fitting the CIR parameters generated by the reference channel model.