Detection of trapped victims using ultrawideband radar is considered a highly challenging task due to multiple unknown parameters and generally very low signal-to-noise-and-clutter ratio (SNCR) conditions. In this paper, we propose a novel detection algorithm which is designed for detection of periodic motion caused by, e.g., respiratory motion of the victim for low SNCR conditions. The aim is to separate the respiratory-motion response of a trapped victim from nonstationary clutter originating from moving objects in the scene of interest. The algorithm performs stationary-clutter removal, high-level noise, and nonstationary-clutter suppression, indicates presence of the trapped victim, and estimates its range. The performance of the algorithm is investigated, both by means of simulation and experimental verification. The results show improved detection capabilities in low SNCR over an existing algorithm proposed by Zaikov et al.@en

Technology of wireless communication has advanced rapidly over the last few years. Much technology developed for this domain of application can be applied to radar. The novelty of the papers is in the anaulysis of the data throughput if the radar signal is coded like a telecommunication message. The message content can for instance consist of the reports on the detected targets. Three types of networking are analysed, based on a network with six identical radars. Frin this analysis it is learned that each radar can transfer an "interesting" number of target reports. Since the dimensions of the radar were chosen rather arbitrarily, much room is open to tailor the specifics of the networked system. Radar-specific issues like the ambiguity function and the observability of the Doppler shift have not been adressed.@en