High precision ranging with IR‐UWB: a compressed sensing approach

• Published in: Wireless communications and mobile computing Vol. 16; no. 17; pp. 3015 - 3031
• Main Authors: Wu, Shaohua, Zhang, Ning, Zhou, Haibo, Zhang, Qinyu, Shen, Xuemin (Sherman)
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 10.12.2016; John Wiley & Sons, Inc
• Subjects: Algorithms; Asymptotic properties; compressed sensing; Error detection; IR‐UWB; low‐rate sampling; Projection; ranging; Sampling; Searching; Thresholds; Ultrawideband
• ISSN: 1530-8669; 1530-8677
• DOI: 10.1002/wcm.2742

Ranging has been regarded as one of the fundamental enabling technologies for a multitude of applications that require high accurate position information, such as automated navigation, vehicle platooning, asset management, etc. Among various ranging techniques, impulse‐radio ultra‐wideband is one of the most competitive technologies for high‐precision ranging, because of its capability of achieving centimeter‐level ranging accuracy, even for dense urban, indoor or cave like environments. However, two main challenges arise when fully exploiting the ranging capability of impulse‐radio ultra‐wideband: (i) the extremely high sampling rate to acquire the received multipath signal, and (ii) the optimal thresholding strategy to differentiate the first path. To efficiently tackle those challenges, in this work, we propose a ranging approach under the compressed sensing framework. Specifically, the received ranging signal is acquired by low‐rate compressed sampling through parallel random projections. Then, an algorithm named matching‐pursuit search‐back is proposed to detect the first arrival path, which integrates a backward iterative search and thresholding process starting from the peak path. The detection threshold is dynamically adjusted in each iteration to asymptotically minimize the averaged detection errors over false alarm and missed detection. Extensive simulations and experiments with field data are provided to demonstrate that the proposed approach can achieve high‐precision ranging with far fewer samples compared with the traditional Nyquist‐sampling based ones. Copyright © 2016 John Wiley & Sons, Ltd. Key findings: an analog front‐end architecture for compressed sampling the IR‐UWB ranging signal, which is structured by parallel multi‐channel random projections; an algorithm named matching‐pursuit search‐back algorithms for time‐of‐arrival estimation from the low‐rate compressed samples, which carries out an iterative backward search from the peak path till the first path being detected; a dynamic threshold setting strategy, jointly considering noise‐related and channel‐related factors, to asymptotically minimize the averaged error over false alarm and missed detection in each iteration of matching‐pursuit search‐back.