The Digital Signal Processing Algorithm Implemented on ARM Embedded System

2013 ◽  
Vol 756-759 ◽  
pp. 3958-3961
Author(s):  
Jian Xiang Chen ◽  
Hong Jun Sun
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Embedded System ◽  
Digital Signal ◽  
Processing Algorithm ◽  
Signal Processing Algorithm ◽  
Signal Processing Algorithms ◽  
Processing Algorithms ◽  
Arm Embedded System ◽  
Digital Signal Processing Algorithm

Digital Signal Processing technology is an important tool for modern signal processing. The speedy development ARM embedded processor has powerful computed capability for digital signal processing algorithms. The paper provides a common hardware platform in recent years. In this paper, used assemble language to realize the algorithms and FIR Filter based on ARM-Linux embedded environment. The results shown that the ARM can quickly and efficiently complete a series of digital signal processing algorithms. Digital signal processing algorithm on ARM embedded system provides an effective way.

scholarly journals Dynamic Digital Signal Processing Algorithm for Vital Signs Extraction in Continuous-Wave Radars

2021 ◽  
Vol 13 (20) ◽  
pp. 4079
Author(s):  
Carolina Gouveia ◽  
Daniel Albuquerque ◽  
José Vieira ◽  
Pedro Pinho
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Continuous Wave ◽  
Vital Signs ◽  
Digital Signal ◽  
Processing Algorithm ◽  
Signal Processing Algorithm ◽  
Radar Systems ◽  
Fitting Method ◽  
Digital Signal Processing Algorithm

Radar systems have been widely explored as a monitoring tool able to assess the subject’s vital signs remotely. However, their implementation in real application scenarios is not straightforward. Received signals encompass parasitic reflections that occur in the monitoring environment. Generally, those parasitic components, often treated as a complex DC (CDC) offsets, must be removed in order to correctly extract the bio-signals information. Fitting methods can be used, but their implementation were revealed to be challenging when bio-signals are weak or when these parasitic reflections arise from non-static targets, changing the CDC offset properties over time. In this work, we propose a dynamic digital signal processing algorithm to extract the vital signs from radar systems. This algorithm includes a novel arc fitting method to estimate the CDC offsets on the received signal. The method revealed being robust to weaker signals, presenting a success rate of 95%, irrespective of the considered monitoring conditions. Furthermore, the proposed algorithm is able to adapt to slow changes in the propagation environment.

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