Next Article in Journal
A Temperature-Hardened Sensor Interface with a 12-Bit Digital Output Using a Novel Pulse Width Modulation Technique
Next Article in Special Issue
Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review
Previous Article in Journal
Adaptive LINE-P: An Adaptive Linear Energy Prediction Model for Wireless Sensor Network Nodes
Previous Article in Special Issue
A Weighted Deep Representation Learning Model for Imbalanced Fault Diagnosis in Cyber-Physical Systems
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle

A Two-Stage Reconstruction Processor for Human Detection in Compressive Sensing CMOS Radar

Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
Institute of Communications Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
Author to whom correspondence should be addressed.
Sensors 2018, 18(4), 1106;
Received: 28 February 2018 / Revised: 2 April 2018 / Accepted: 3 April 2018 / Published: 5 April 2018
(This article belongs to the Special Issue Sensor Signal and Information Processing)
PDF [1322 KB, uploaded 3 May 2018]


Complementary metal-oxide-semiconductor (CMOS) radar has recently gained much research attraction because small and low-power CMOS devices are very suitable for deploying sensing nodes in a low-power wireless sensing system. This study focuses on the signal processing of a wireless CMOS impulse radar system that can detect humans and objects in the home-care internet-of-things sensing system. The challenges of low-power CMOS radar systems are the weakness of human signals and the high computational complexity of the target detection algorithm. The compressive sensing-based detection algorithm can relax the computational costs by avoiding the utilization of matched filters and reducing the analog-to-digital converter bandwidth requirement. The orthogonal matching pursuit (OMP) is one of the popular signal reconstruction algorithms for compressive sensing radar; however, the complexity is still very high because the high resolution of human respiration leads to high-dimension signal reconstruction. Thus, this paper proposes a two-stage reconstruction algorithm for compressive sensing radar. The proposed algorithm not only has lower complexity than the OMP algorithm by 75% but also achieves better positioning performance than the OMP algorithm especially in noisy environments. This study also designed and implemented the algorithm by using Vertex-7 FPGA chip (Xilinx, San Jose, CA, USA). The proposed reconstruction processor can support the 256 × 13 real-time radar image display with a throughput of 28.2 frames per second. View Full-Text
Keywords: compressive sensing; CMOS radar; ranging compressive sensing; CMOS radar; ranging

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Tsao, K.-C.; Lee, L.; Chu, T.-S.; Huang, Y.-H. A Two-Stage Reconstruction Processor for Human Detection in Compressive Sensing CMOS Radar. Sensors 2018, 18, 1106.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top