This letter presents a gait classification technique for the identification of individuals with different gait patterns using simulated micro-Doppler radar remote sensing data. Proposed feature parameters for the classification are principal components of velocities extracted via micro-Doppler radar signals generated using motion capture-based kinematic data. Distinct differences were found in the proposed parameters among three groups of subjects with different gait patterns: healthy young and elderly adults, and elderly adults with a history of falls (elderly fallers).