Pedestrian safety is one of the major tasks of automotive radars. Pedestrian detection in practical urban scenarios is challenging task due to the strong vertical and horizontal multipath phenomena from the asphalt roads and surrounding buildings, proximity to other obstacles with highradar cross section, and high probability of blockage by other targets. This work addresses the problem of joint pedestrian detection and classification in a practical urban environment by a 24 GHz FMCW automotive radar. The urban RF environment consisting of the asphalt road, vehicles and pedestrian was simulated. Micro-Doppler analysis was used to discriminate between pedestrians, vehicles, and animals. A variety of human activities, including mixed motion sequences were tested in target classification simulations.