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Item type:Publication, Access status: without files , Track-before-detect short range radar system for industrial applicationsThis paper presents a multiplexed short range frequency modulated continuous wave (FMCW) radar system and an algorithmic approach for the detection of targets. The algorithm uses a heuristic particle filter to track potential targets before they are actually detected. The detection algorithm is compared to a well-known constant false alarm rate (CFAR) detector. The whole setup is tested on real-life data in an industrial scenario.Publicationtype: Conference Paper237 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , On the impact of system nonlinearities in continuous-wave radar systems for vital parameter sensingThis paper investigates the influence of nonlinearities on relative distance measurements by continuous-wave radar systems. For the case of a six-port receiver architecture, a mathematical relationship between detector nonlinearity and measurement error is derived. Moreover, a generalized sinusoidal error model, which fits both six-port and mixer-based radar systems, is used to study the effect of nonlinear mixing when one or more displacement movements with different amplitudes are to be detected.Publicationtype: Conference Paper340 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Low-cost direction-of-arrival measurements using multiplexed antenna switchingIn this publication a method for direction-of-arrival measurements is introduced. It allows very low cost implementations. Instead of using multiple wide-band receivers with an antenna each, a single narrow-band receiver is used in combination with six antennas. The different antenna signals are time multiplexed to the receiver using an integrated 6-to-l RF switch. Signal processing allows to synchronize the corresponding signals to allow the calculation of the incident angle. As exact synchronization is not necessary, fast transitions between multiple frequencies are possible and therefore accuracy can be significantly increased.Publicationtype: Conference Paper103 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Uncertainty analysis of deep neural network for classification of vulnerable road users using micro-dopplerUnlike optical imaging, it's difficult to extract descriptive features from radar data for problems like classification of different targets. This paper takes the advantage of different neural network based architectures such as convolutional neural networks and long-short term memory to propose an end-to-end framework for classification of vulnerable road users. To make the network's prediction more reliable for automotive applications, a new concept of network uncertainty is introduced to the defined architectures. The signal processing tool chain described in this paper achieves higher accuracy than state-of-the-art algorithms while maintaining latency requirement for automotive applications.Publicationtype: Conference Paper135