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Remote-sensing radar methods are used in many fields of application e.g., in environment and traffic engineering for glacier monitoring or observation of unstable slopes or in facility management for assessing the stability of buildings. In industry and agriculture, they are used for automatic detection of small deviations and are thus helpful in developing new quality assurance systems. So-called MIMO (Multiple Input Multiple Output) radar systems or sensor networks can be used for measurements with a particularly high spatial resolution. Such systems are provided with several spatially distributed transmitting aerials each of which can emit an arbitrary transmission signal that can be received by any receiving aerial. The large number of signaling paths thus created allows comprehensive surveying of the respective scenarios. To be able to reconstruct the individual receiver-side distribution paths, the different transmission signals must be clearly separable. Typically, signal separation is achieved by bundling with respect to temporal transmission or by a certain coding (time multiplexing and code multiplexing). Researchers at Institute for High-frequency Engineering and Electronic Engineering (IHE) separate and bundle signals in a new way to improve the dynamics and resolution of MIMO radar systems. To do so, the subcarriers of a multicarrier signal are distributed to the different transmitting aerials according to a certain scheme. The signals generated in that way are interleaved in the spectral range without reducing the system bandwidth of the individual transmitters (spectrally interleaved multicarrier). The new method ensures a complete separability of signals while maintaining the entire signal bandwidth and, thus, has decisive advantages over the classical time and code multiplexing methods. Unlike time multiplexing, the new MIMO radars allow simultaneous activity of several transmitters at a time and, thus, surveying of moving or changing objects. The new method allows achieving considerably higher dynamics as compared to code multiplexing.
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Karlsruhe Institute of Technology (KIT)
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