Abstract: To accurately characterize the wireless channel propagation characteristics between nodes in a Mobile Ad Hoc Network (MANET) under low antenna height conditions within complex urban street canyon environments at 5.8 GHz, and to address the challenges in simulating channel models where tap amplitudes exhibit non-Gaussian distributions while preserving the Doppler correlation structure, this paper presents a measurement-based channel modeling and simulation study. First, a high-precision wideband measurement system is established to capture the time-varying channel impulse response (CIR). Subsequently, the tapped delay line (TDL) channel model is developed using the space-alternating generalized expectation-maximization (SAGE) algorithm in conjunction with the Akaike Information Criterion (AIC). Modeling results reveal significant differences in channel statistics between line-of-sight (LoS) and non-line-of-sight (NLoS) conditions: NLoS propagation, dominated by dense scattering and diffraction, exhibits a root mean square delay spread (RMS-DS) of 409 ns, considerably larger than the LoS value of 197 ns, while the corresponding coherence bandwidth decreases from 1.149 MHz to 0.508 MHz. To enable time-variant simulation of the model, a statistically consistent channel simulation method based on Copula theory is further proposed. This method employs a complex Gaussian reference process to carry the target Doppler power spectral density (DPSD). Through probability integral transform (pit) and inverse distribution mapping, it achieves rigorous embedding of arbitrary amplitude distributions while preserving time-varying correlation via phase inheritance, thereby decoupling amplitude distribution from temporal correlation. Results demonstrate that this approach simultaneously replicates the target amplitude distribution and DPSD characteristics, achieving a Kolmogorov-Smirnov (K-S) distance below 0.01 for amplitude consistency and a normalized mean square error (NMSE) better than −18 dB for DPSD consistency. The method accurately reproduces the statistical characteristics of complex urban channel models, providing robust channel modeling and simulation support for communication system design.