Design and implementation of proposed pipelined adaptive recovery CAMP algorithm for LFMCW radar
Recently, Compressive Sensing (CS) theory based on the traditional CAMP reconstruction algorithm has applied in radar systems to achieve the benefits of CS such as low sampling rate, small memory size, less complexity in hardware and consequently reduces the required processing time as using a low s...
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          | Published in | Signal, image and video processing Vol. 15; no. 2; pp. 271 - 278 | 
|---|---|
| Main Author | |
| Format | Journal Article | 
| Language | English | 
| Published | 
        London
          Springer London
    
        01.03.2021
     Springer Nature B.V  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 1863-1703 1863-1711  | 
| DOI | 10.1007/s11760-020-01741-0 | 
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| Abstract | Recently, Compressive Sensing (CS) theory based on the traditional CAMP reconstruction algorithm has applied in radar systems to achieve the benefits of CS such as low sampling rate, small memory size, less complexity in hardware and consequently reduces the required processing time as using a low speed Analog-to-Digital Converter. A modified reconstruction Complex Approximate Massage Passing (CAMP) algorithm designed as an adaptive recovery algorithm is introduced. The adaptive recovery algorithm depends on selecting the comparison threshold in an adaptive manner resembling the Constant False Alarm Rate processing. In this paper, design and implementation of the adaptive algorithm for Linear Frequency Modulated Continuous Wave radar signals are achieved using Field Programmable Gate Array (FPGA). A proposed pipelined process-based scheme is used in the implementation that leads to a more redundant in complexity and processing time. A generic methodology based on segmenting the acquired radar signal and applying the adaptive recovery algorithm on each segment is proposed. This method enables the investigation of the adaptive recovery algorithm on any signal length with fixed hardware resources. A suggested processing method is implemented called pipelined adaptive recovery CAMP algorithm, which enhances the performance of reconstructing the radar signal better than the traditional CAMP algorithm. Hardware implementation using FPGA and experiments are met, and their results agree very well with the simulation outcomes. | 
    
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| AbstractList | Recently, Compressive Sensing (CS) theory based on the traditional CAMP reconstruction algorithm has applied in radar systems to achieve the benefits of CS such as low sampling rate, small memory size, less complexity in hardware and consequently reduces the required processing time as using a low speed Analog-to-Digital Converter. A modified reconstruction Complex Approximate Massage Passing (CAMP) algorithm designed as an adaptive recovery algorithm is introduced. The adaptive recovery algorithm depends on selecting the comparison threshold in an adaptive manner resembling the Constant False Alarm Rate processing. In this paper, design and implementation of the adaptive algorithm for Linear Frequency Modulated Continuous Wave radar signals are achieved using Field Programmable Gate Array (FPGA). A proposed pipelined process-based scheme is used in the implementation that leads to a more redundant in complexity and processing time. A generic methodology based on segmenting the acquired radar signal and applying the adaptive recovery algorithm on each segment is proposed. This method enables the investigation of the adaptive recovery algorithm on any signal length with fixed hardware resources. A suggested processing method is implemented called pipelined adaptive recovery CAMP algorithm, which enhances the performance of reconstructing the radar signal better than the traditional CAMP algorithm. Hardware implementation using FPGA and experiments are met, and their results agree very well with the simulation outcomes. | 
    
| Author | Salem, Sameh G. | 
    
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| Keywords | Compressive sensing Xampling Pipeline process FMCW radar Adaptive CAMP algorithm  | 
    
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| References | Donoho (CR1) 2006; 52 Baraniuk, Steeghs (CR2) 2007; 24 Herman, Strohmer (CR3) 2009; 57 CR6 CR7 CR18 Mishali, Eldar, Elron (CR19) 2011; 59 CR16 Salem, Ahmed, Ibrahim, Elbardawiny (CR11) 2015; 4 CR15 Maravic, Vetterli (CR20) 2005; 53 CR14 Liu, Liu, Gao, Wang, Wang (CR9) 2020 CR13 Liu, Sun, Liu (CR8) 2019; 67 CR12 CR10 CR21 Hossiny, Salem, Ahmed, Moustafa (CR4) 2017 Maleki, Anitori (CR17) 2011; 57 Eldar (CR5) 2009; 57 1741_CR6 W Liu (1741_CR9) 2020 1741_CR16 MH Hossiny (1741_CR4) 2017 1741_CR7 1741_CR18 A Maleki (1741_CR17) 2011; 57 DL Donoho (1741_CR1) 2006; 52 YC Eldar (1741_CR5) 2009; 57 SG Salem (1741_CR11) 2015; 4 MA Herman (1741_CR3) 2009; 57 I Maravic (1741_CR20) 2005; 53 J Liu (1741_CR8) 2019; 67 1741_CR13 1741_CR12 1741_CR15 1741_CR14 RG Baraniuk (1741_CR2) 2007; 24 1741_CR10 M Mishali (1741_CR19) 2011; 59 1741_CR21  | 
    
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| SubjectTerms | Adaptive algorithms Algorithms Analog to digital conversion Analog to digital converters Complexity Computer Imaging Computer Science Constant false alarm rate Continuous wave radar Field programmable gate arrays Hardware Image Processing and Computer Vision Low speed Multimedia Information Systems Original Paper Pattern Recognition and Graphics Radar equipment Reconstruction Recovery Signal processing Signal,Image and Speech Processing Vision  | 
    
| Title | Design and implementation of proposed pipelined adaptive recovery CAMP algorithm for LFMCW radar | 
    
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