{"id":3215,"date":"2023-06-13T11:25:53","date_gmt":"2023-06-13T09:25:53","guid":{"rendered":"https:\/\/greenict.de\/?p=3215"},"modified":"2024-01-10T10:44:49","modified_gmt":"2024-01-10T09:44:49","slug":"signalprocessing-on-the-edge-%c2%b5controller-basierte-radar-back-end-struktur","status":"publish","type":"post","link":"https:\/\/greenict.de\/en\/signalprocessing-on-the-edge-%c2%b5controller-basierte-radar-back-end-struktur\/","title":{"rendered":"Signal processing on the edge \u2013 \u00b5Controller-based radar back-end structure\u00a0"},"content":{"rendered":"<p><strong>The FHR has developed a new back-end structure for its radar sensors, which can be switched off, extended, and reconfigured at runtime by their master\/slave configuration. In addition, signal processing by interpolation has been adapted so that it can be performed directly \"on the edge\" on the \u00b5Controller.&nbsp;<\/strong><\/p>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"wp-block-media-text alignwide is-stacked-on-mobile is-vertically-aligned-center\" style=\"grid-template-columns:35% auto\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"1024\" src=\"https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Andre-Knieps-1024x1024.jpg\" alt=\"\" class=\"wp-image-3227 size-full\" srcset=\"https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Andre-Knieps-1024x1024.jpg 1024w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Andre-Knieps-300x300.jpg 300w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Andre-Knieps-150x150.jpg 150w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Andre-Knieps-768x768.jpg 768w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Andre-Knieps-1536x1536.jpg 1536w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Andre-Knieps-2048x2048.jpg 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<p class=\"translation-block\">An article by Michel Andre Knieps, M.Sc.\nDepartment Embedded Systems\nIndustrial High Frequency Systems Division (IHS)<br>\n<a href=\"https:\/\/www.fhr.fraunhofer.de\/\" target=\"_blank\" rel=\"noreferrer noopener external\" data-wpel-link=\"external\" class=\"wpel-icon-right\">Fraunhofer FHR<span class=\"wpel-icon wpel-image wpel-icon-6\"><\/span><\/a><\/p>\n<\/div><\/div>\n\n\n\n<div style=\"height:10px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><\/p>\n\n\n\n<p>FHR focuses on the conceptual design of distributed signal processing systems both in the distribution of energy-efficient interconnected sensors, and in the conceptual design for energy-efficient distribution of signal processing to the hardware and software components across the sensor edge cloud components. A radar-based example demonstrator will be realized in the course of the project and will represent a four-channel radar sensor equipped with two \u00b5controllers. These \u00b5controller-based networked sensor nodes and the respective firmware development represent the main work of FHR. Four connected phase coherent radar nodes (80GHz\/ 140 GHz) are controlled and scanned by two networked \u00b5controllers, which will be operated in master \/ slave configuration. Both the sensor nodes and the slave \u00b5controller will be able to be switched on and off by the master \u00b5controller. The four ADC channels are also configurable to support 1-4 channel operation in the standard sampling rate as well as 1-2 channel operation in \"interleaved\" mode for up to two sensor nodes at twice the sampling rate.&nbsp;<\/p>\n\n\n\n<p>By developing new back-end structures, where each board contains a \u00b5controller, the system becomes further scalable. This means that not only a slave \u00b5controller is conceivable, but the system can be expanded. For scenarios where more than four channels are required, the overall system can be expanded with additional slave \u00b5controllers. The development of the board is shown in figure 1 and 2.<\/p>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:450px\">\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"760\" height=\"629\" src=\"https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Vorderansicht-neues-Back-End-Radarsensor.jpg\" alt=\"\" class=\"wp-image-3216\" srcset=\"https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Vorderansicht-neues-Back-End-Radarsensor.jpg 760w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Vorderansicht-neues-Back-End-Radarsensor-300x248.jpg 300w\" sizes=\"auto, (max-width: 760px) 100vw, 760px\" \/><figcaption class=\"wp-element-caption\">Figure 1: Front view of new back-end\nradar sensor \u00a9 Fraunhofer FHR<\/figcaption><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:361px\">\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" src=\"https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/rueckansicht-neues-back-end-radarsensor.jpg\" alt=\"\" class=\"wp-image-3239\"\/><figcaption class=\"wp-element-caption\">Figure 2: Rear view of new back-end radar sensor \u00a9 Fraunhofer FHR<\/figcaption><\/figure>\n<\/div>\n<\/div>\n\n\n\n<p>In order to measure distances, it is necessary to process the incoming signals from the radar sensors. The processing mainly refers to different types of real, complex, and inverse Fourier transforms. Since the maximum amplitude in the spectrum of the resulting intermediate frequency correlates directly with the distance to the measured object, large block sizes of the Fourier transform are often required. The reason for this is the degree of resolution for frequency estimation in the spectrum because the resolution capacity depends on the sampling frequency and the total number of interpolation points in the spectrum. On \u00b5Controller structures, large block sizes can often not be implemented efficiently. Therefore, an interpolation method keeps the resolving power equivalent with decreasing block sizes. This interpolation method is based on a quadratic interpolation in the frequency domain. A simple reduction of the block sizes would lead to inaccuracies concerning the distance evaluation. Thus, saving computing power while maintaining the same accuracy is important. Another advantage of an interpolation method is based on the possibility of performing the frequency estimation in the spectrum continuously instead of discretely.&nbsp;&nbsp;<\/p>\n\n\n\n<p>Two simulations were performed to validate the consistent accuracy. The first simulation refers to verifying the simple reduction of the block size without the interpolation approach (Figure 3). Figure 4 presents the results of a simulation with an interpolation approach. It shows that the results without interpolation cannot be used. The measure of the same accuracy does not fit because the deviation is more significant than with an implementation with a 16k Fourier transform.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"561\" src=\"https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Verkleinerung-der-FFT-Blockgrose-mit-verschiedenen-Blockgrosen-1024x561.jpg\" alt=\"\" class=\"wp-image-3225\" srcset=\"https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Verkleinerung-der-FFT-Blockgrose-mit-verschiedenen-Blockgrosen-1024x561.jpg 1024w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Verkleinerung-der-FFT-Blockgrose-mit-verschiedenen-Blockgrosen-300x164.jpg 300w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Verkleinerung-der-FFT-Blockgrose-mit-verschiedenen-Blockgrosen-768x421.jpg 768w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Verkleinerung-der-FFT-Blockgrose-mit-verschiedenen-Blockgrosen-1536x841.jpg 1536w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Verkleinerung-der-FFT-Blockgrose-mit-verschiedenen-Blockgrosen.jpg 1649w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Figure 3: FFT block size reduction with different block sizes. \u00a9 Fraunhofer FHR<\/figcaption><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"560\" src=\"https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Interpolationsansatz-1024x560.jpg\" alt=\"\" class=\"wp-image-3226\" srcset=\"https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Interpolationsansatz-1024x560.jpg 1024w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Interpolationsansatz-300x164.jpg 300w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Interpolationsansatz-768x420.jpg 768w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Interpolationsansatz-1536x840.jpg 1536w, https:\/\/greenict.de\/wp-content\/uploads\/2023\/06\/Interpolationsansatz.jpg 1656w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Figure 4: Interpolation approach with reduction of FFT block sizes for different block sizes. \n\u00a9 Fraunhofer FHR<\/figcaption><\/figure>","protected":false},"excerpt":{"rendered":"<p>Fraunhofer FHR \u2013 The FHR has developed a new back-end structure for its radar sensors, which can be switched off, extended, and reconfigured at runtime by their master\/slave configuration. In addition, signal processing by interpolation has been adapted so that it can be performed directly \"on the edge\" on the \u00b5Controller. <\/p>","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[39,36,38,37],"class_list":["post-3215","post","type-post","status-publish","format-standard","hentry","category-allgemein","tag-energieeffizienz","tag-radar","tag-signalverarbeitung","tag-controller"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Signalprocessing on the edge - \u00b5Controller basierte Radar Back-End Struktur\u00a0<\/title>\n<meta name=\"description\" content=\"Das FHR hat eine Back-End Struktur f\u00fcr eigene Radarsensoren entwickelt, die sich durch ihre Master\/Slave Konfiguration zur Laufzeit abschalten, erweitern und umkonfigurieren lassen\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/greenict.de\/en\/signalprocessing-on-the-edge-\u00b5controller-basierte-radar-back-end-struktur\/\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/greenict.de\\\/signalprocessing-on-the-edge-%c2%b5controller-basierte-radar-back-end-struktur\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/greenict.de\\\/signalprocessing-on-the-edge-%c2%b5controller-basierte-radar-back-end-struktur\\\/\"},\"author\":{\"name\":\"Christina F\u00f6rster\",\"@id\":\"https:\\\/\\\/greenict.de\\\/#\\\/schema\\\/person\\\/fef21d45d931b4ef484eb04b19df385a\"},\"headline\":\"Signalprocessing on the edge &#8211; 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