Design and implementation of proposed pipelined adaptive recovery CAMP algorithm for LFMCW radar.

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Author: Sameh G. Salem
Date: Mar. 2021
From: Signal, Image and Video Processing(Vol. 15, Issue 2)
Publisher: Springer
Document Type: Report; Brief article
Length: 260 words

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Abstract :

Keywords: Compressive sensing; FMCW radar; Adaptive CAMP algorithm; Xampling; Pipeline process 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. Author Affiliation: (1) Egyptian Academy for Engineering and Advanced Technology (EAEAT), Cairo, Egypt (a) Article History: Registration Date: 07/09/2020 Received Date: 10/10/2019 Accepted Date: 07/09/2020 Online Date: 07/29/2020 Byline:

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Gale Document Number: GALE|A651735660