A VLSI design of singular value decomposition processor for portable continuous-wave diffusion optical tomography systems

2011 ◽  
Author(s):  
Shih Kang ◽  
Shih-Yang Wu ◽  
Yuan-Huang Hsu ◽  
Chih-Chung Fu ◽  
Wai-Chi Fang
Keyword(s):  
Singular Value Decomposition ◽  
Continuous Wave ◽  
Optical Tomography ◽  
Vlsi Design ◽  
Singular Value ◽  
Wave Diffusion ◽  
Value Decomposition

scholarly journals High Accuracy Heartbeat Detection from CW-Doppler Radar Using Singular Value Decomposition and Matched Filter

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3588
Author(s):  
Yuki Iwata ◽  
Han Trong Thanh ◽  
Guanghao Sun ◽  
Koichiro Ishibashi
Keyword(s):  
Heart Rate ◽  
Singular Value Decomposition ◽  
Continuous Wave ◽  
Doppler Radar ◽  
Matched Filter ◽  
Singular Value ◽  
Home Healthcare ◽  
Body Motion ◽  
Sitting Posture ◽  
Value Decomposition

Heart rate measurement using a continuous wave Doppler radar sensor (CW-DRS) has been applied to cases where non-contact detection is required, such as the monitoring of vital signs in home healthcare. However, as a CW-DRS measures the speed of movement of the chest surface, which comprises cardiac and respiratory signals by body motion, extracting cardiac information from the superimposed signal is difficult. Therefore, it is challenging to extract cardiac information from superimposed signals. Herein, we propose a novel method based on a matched filter to solve this problem. The method comprises two processes: adaptive generation of a template via singular value decomposition of a trajectory matrix formed from the measurement signals, and reconstruction by convolution of the generated template and measurement signals. The method is validated using a dataset obtained in two different experiments, i.e., experiments involving supine and seated subject postures. Absolute errors in heart rate and standard deviation of heartbeat interval with references were calculated as 1.93±1.76bpm and 57.0±28.1s for the lying posture, and 9.72±7.86bpm and 81.3±24.3s for the sitting posture.

scholarly journals Through Wall Radar Classification of Human Micro-Doppler using Singular Value Decomposition Analysis

2016 ◽  
Author(s):  
Matthew Ritchie ◽  
Matthew Ash ◽  
Qingchao Chen ◽  
Kevin Chetty
Keyword(s):  
Singular Value Decomposition ◽  
Emergency Services ◽  
Continuous Wave ◽  
Decomposition Analysis ◽  
Residential Building ◽  
Singular Value ◽  
Singular Value Decomposition Analysis ◽  
Radar Sensors ◽  
Value Decomposition ◽  
Processing Techniques

The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques.

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