Modeling the Magnitude and Phase of Multipath UWB Signals for the Use in Passive Localization

Radio-frequency (RF)-based device-free localization (DFL) systems measure RF parameters such as the received signal strength or channel state information to detect and track objects within a certain area. However, the change of the RF signal caused by the object is superimposed with various changes of the RF signal due to multipath propagation, especially in indoor environments. In this paper, we develop a model for ultra-wideband (UWB) channel impulse response (CIR) measurements for application in DFL systems. The model predicts received signal parameters in a setup with a transmitter and a receiver node, a person and multipath propagation. Different from other approaches, the RF hardware, and the model provides both magnitude and phase information for individual multipath components. We evaluate the new model with real measurements that have been conducted with a Decawave DW1000 radio chip. For the magnitudes, we achieved a correlation factor from 0.78 to 0.87 and maximum mean and standard deviation errors of 1.7 dB and 2.2 dB respectively. For the phase, we achieved correlation factor from 0.6 to 0.81 and maximum mean and standard deviation errors of 0.32 dB and 0.47 dB respectively, showing that the prediction of our proposed model for the magnitude and phase fits well to our measurements.

[1]  Ossi Kaltiokallio,et al.  A Three-State Received Signal Strength Model for Device-Free Localization , 2014, IEEE Transactions on Vehicular Technology.

[2]  Christian Gentner,et al.  Localization of Discrete Mobile Scatterers in Vehicular Environments Using Delay Estimates , 2019, 2019 International Conference on Localization and GNSS (ICL-GNSS).

[3]  Horst Hellbrück,et al.  Modeling received signal strength and multipath propagation effects of moving persons , 2017, 2017 14th Workshop on Positioning, Navigation and Communications (WPNC).

[4]  Monica Nicoli,et al.  Pre-deployment performance assessment of device-free radio localization systems , 2016, 2016 IEEE International Conference on Communications Workshops (ICC).

[5]  Kay Römer,et al.  SALMA: UWB-based Single-Anchor Localization System using Multipath Assistance , 2018, SenSys.

[6]  Moe Z. Win,et al.  High-Accuracy Localization for Assisted Living: 5G systems will turn multipath channels from foe to friend , 2016, IEEE Signal Processing Magazine.

[7]  Horst Hellbrück,et al.  Sundew: Design and Evaluation of a Model-Based Device-Free Localization System , 2018, 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[8]  Jianping An,et al.  Towards robust and efficient device-free localization using UWB sensor network , 2017, Pervasive Mob. Comput..

[9]  Horst Hellbrück,et al.  Evaluation of time-based ranging methods: Does the choice matter? , 2017, 2017 14th Workshop on Positioning, Navigation and Communications (WPNC).

[10]  Henk Wymeersch,et al.  Device-Free Person Detection and Ranging in UWB Networks , 2013, IEEE Journal of Selected Topics in Signal Processing.

[11]  Horst Hellbrück,et al.  On the Effective Length of Channel Impulse Responses in UWB Single Anchor Localization , 2019, 2019 International Conference on Localization and GNSS (ICL-GNSS).

[12]  Axel Sikora,et al.  Investigations on passive channel impulse response of ultra wide band signals for monitoring and safety applications , 2016, 2016 3rd International Symposium on Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS).

[13]  Milad Heydariaan,et al.  Device-Free Activity Recognition Using Ultra-Wideband Radios , 2019, 2019 International Conference on Computing, Networking and Communications (ICNC).