Human activity characterization based on gait signatures is important in several applications including medical, elderly care, police, biometric identification, etc. Cameras and on-body accelerometers are widely investigated for characterizing human activity. Nonetheless, in order to achieve wide acceptance, sensors to be used for these applications should be unobtrusive and people's privacy should be respected. Radar is a promising technology for human activity characterization as it satisfies these requirements and operates largely unaffected by environmental conditions and the presence of blocking objects. This thesis presents algorithms for radar signal processing and human activity quantification, identification and classification in indoor environment. Methods to extract parameters of human motion such as activity level, displacement, velocity, step length, velocity bandwidth, etc., from radar data are suggested and discussed. The developed algorithms are evaluated in an experimental low-cost radar prototype using Universal Software Radio Peripheral and GNU Radio.