Signal processing architectures for automotive high-resolution MIMO radar systems

To date, the digital signal processing for an automotive radar sensor has been handled in an efficient way by general purpose signal processors and microcontrollers. However, increasing resolution requirements for automated driving on the one hand, as well as rapidly growing numbers of manufactured sensors on the other hand, can provoke a paradigm change in the near future. The design and development of highly specialized hardware accelerators could become a viable option - at least for the most demanding processing steps with data rates of several gigabits per second. In this work, application-specific signal processing architectures for future high-resolution multiple-input and multiple-output (MIMO) radar sensors are designed, implemented, investigated and optimized. A focus is set on real-time performance such that even sophisticated algorithms can be computed sufficiently fast. The full processing chain from the received baseband signals to a list of detections is considered, comprising three major steps: Spectrum analysis, target detection and direction of arrival estimation. The developed architectures are further implemented on a field-programmable gate array (FPGA) and important measurements like resource consumption, power dissipation or data throughput are evaluated and compared with other examples from literature. A substantial dataset, based on more than 3600 different parametrizations and variants, has been established with the help of a model-based design space exploration and is provided as part of this work. Finally, an experimental radar sensor has been built and is used under real-world conditions to verify the effectiveness of the proposed signal processing architectures.Bisher wurde die digitale Signalverarbeitung für automobile Radarsensoren auf eine effiziente Art und Weise von universell verwendbaren Mikroprozessoren bewältigt. Jedoch können steigende Anforderungen an das Auflösungsvermögen für hochautomatisiertes Fahren einerseits, sowie schnell wachsende Stückzahlen produzierter Sensoren andererseits, einen Paradigmenwechsel in naher Zukunft bewirken. Die Entwicklung von hochgradig spezialisierten Hardwarebeschleunigern könnte sich als eine praktikable Alternative etablieren - zumindest für die anspruchsvollsten Rechenschritte mit Datenraten von mehreren Gigabits pro Sekunde. In dieser Arbeit werden anwendungsspezifische Signalverarbeitungsarchitekturen für zukünftige, hochauflösende, MIMO Radarsensoren entworfen, realisiert, untersucht und optimiert. Der Fokus liegt dabei stets auf der Echtzeitfähigkeit, sodass selbst anspruchsvolle Algorithmen in einer ausreichend kurzen Zeit berechnet werden können. Die komplette Signalverarbeitungskette, beginnend von den empfangenen Signalen im Basisband bis hin zu einer Liste von Detektion, wird in dieser Arbeit behandelt. Die Kette gliedert sich im Wesentlichen in drei größere Teilschritte: Spektralanalyse, Zieldetektion und Winkelschätzung. Des Weiteren werden die entwickelten Architekturen auf einem FPGA implementiert und wichtige Kennzahlen wie Ressourcenverbrauch, Stromverbrauch oder Datendurchsatz ausgewertet und mit anderen Beispielen aus der Literatur verglichen. Ein umfangreicher Datensatz, welcher mehr als 3600 verschiedene Parametrisierungen und Varianten beinhaltet, wurde mit Hilfe einer modellbasierten Entwurfsraumexploration erstellt und ist in dieser Arbeit enthalten. Schließlich wurde ein experimenteller Radarsensor aufgebaut und dazu benutzt, die entworfenen Signalverarbeitungsarchitekturen unter realen Umgebungsbedingungen zu verifizieren

Improved Multi-Scale Grid Rendering of Point Clouds for Radar Object Detection Networks

Architectures that first convert point clouds to a grid representation and then apply convolutional neural networks achieve good performance for radar-based object detection. However, the transfer from irregular point cloud data to a dense grid structure is often associated with a loss of information, due to the discretization and aggregation of points. In this paper, we propose a novel architecture, multi-scale KPPillarsBEV, that aims to mitigate the negative effects of grid rendering. Specifically, we propose a novel grid rendering method, KPBEV, which leverages the descriptive power of kernel point convolutions to improve the encoding of local point cloud contexts during grid rendering. In addition, we propose a general multi-scale grid rendering formulation to incorporate multi-scale feature maps into convolutional backbones of detection networks with arbitrary grid rendering methods. We perform extensive experiments on the nuScenes dataset and evaluate the methods in terms of detection performance and computational complexity. The proposed multi-scale KPPillarsBEV architecture outperforms the baseline by 5.37% and the previous state of the art by 2.88% in Car AP4.0 (average precision for a matching threshold of 4 meters) on the nuScenes validation set. Moreover, the proposed single-scale KPBEV grid rendering improves the Car AP4.0 by 2.90% over the baseline while maintaining the same inference speed.Comment: (c) 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Hybridisierungskinetiken von Oligo- und Polynukleotiden an Glas-Oberflächen

Cytosolische Sulfotransferasen katalysieren den Transfer der Sulfonatgruppe auf endogene Verbindungen wie z.B. Steroide oder Katecholamine sowie auf Xenobiotika. Die Sulfonierung bestimmter Substanzen führt abhängig von deren Struktur jedoch zur Bildung reaktiver, mutagener and carcinogener Metaboliten. Im SULT1A1-Gen wurden Punktmutationen ('Single-Nucleotide-Polymorphisms', SNPs) identifiziert, die zu Aminosäureaustausch führen. Der am häufigsten vorkommende Austausch G638A führt zu den beiden Alloenzymen SULT1A1*Arg213 und *His213. Um mögliche Assoziationen zwischen Krankheitsbildern und bestimmten SULT1A1 Genotypen feststellen zu können, ist eine Untersuchungsmethode notwendig, bei der in kurzer Zeit der Genotyp möglichst vieler Probanden ermittelt werden kann. Daher soll anhand des Modells der humanen Sulfotransferase SULT1A1 der Einfluß von Punktmutationen auf das Hybridisierungsverhalten von Oligo- und Polynukleotiden untersucht werden. Diese Untersuchungen dienen als Vorversuche für die Etablierung und Automatisierung der SNP-Analyse auf DNA-Chips, die den gewünschten Probendurchsatz ermöglichen soll. Die SNP-Analyse erfolgt mittels Glasfaser-Optik. Auf einer streptavidinbeschichteten Glasfaser-Oberfläche ist ein 13 Bp langes Oligonukleotid - der SNP und 12 flankierende Nukleotide - über Biotin immobilisiert. Nach Zugabe eines mit Fluorescein gelabelten Proben-Amplifikats findet die Hybridisierung am 13mer statt. Anschließend wird durch Spülen mit Puffer die Dissoziation des Polynukleotids ausgelöst. Anhand des emittierten Fluoreszenz-Signals kann die Reaktionsgeschwindigkeitskonstante der Dissoziation bestimmt werden. Es konnte gezeigt werden, daß sich die Dissoziationsgeschwindigkeit eines mis-match (Bsp. Mutante - Wildtyp) wesentlich von der eines full-match (Bsp. Mutante - Mutante) unterscheidet. Es ist somit möglich, anhand der Dissoziationskinetik Mutante und Wildtyp eines SNP-haltigen DNA-Abschnitts zu identifizieren

BAFF is produced by astrocytes and up-regulated in multiple sclerosis lesions and primary central nervous system lymphoma

We report that B cell–activating factor of the tumor necrosis factor (TNF) family (BAFF) is expressed in the normal human brain at ∼10% of that in lymphatic tissues (tonsils and adenoids) and is produced by astrocytes. BAFF was regularly detected by enzyme-linked immunosorbent assay in brain tissue lysates and in normal spinal fluid, and in astrocytes by double fluorescence microscopy. Cultured human astrocytes secreted functionally active BAFF after stimulation with interferon-γ and TNF-α via a furin-like protease-dependent pathway. BAFF secretion per cell was manifold higher in activated astrocytes than in monocytes and macrophages. We studied brain lesions with B cell components, and found that in multiple sclerosis plaques, BAFF expression was strongly up-regulated to levels observed in lymphatic tissues. BAFF was localized in astrocytes close to BAFF-R–expressing immune cells. BAFF receptors were strongly expressed in situ in primary central nervous system (CNS) lymphomas. This paper identifies astrocytes as a nonimmune source of BAFF. CNS-produced BAFF may support B cell survival in inflammatory diseases and primary B cell lymphoma

Fingolimod induces neuroprotective factors in human astrocytes.

Background Fingolimod (FTY720) is the first sphingosine-1-phosphate (S1P) receptor modulator approved for the treatment of multiple sclerosis. The phosphorylated active metabolite FTY720-phosphate (FTY-P) interferes with lymphocyte trafficking. In addition, it accumulates in the CNS and reduces brain atrophy in multiple sclerosis (MS), and neuroprotective effects are hypothesized. Methods Human primary astrocytes as well as human astrocytoma cells were stimulated with FTY-P or S1P. We analyzed gene expression by a genome-wide microarray and validated induced candidate genes by quantitative PCR (qPCR) and ELISA. To identify the S1P-receptor subtypes involved, we applied a membrane-impermeable S1P analog (dihydro-S1P), receptor subtype specific agonists and antagonists, as well as RNAi silencing. Results FTY-P induced leukemia inhibitory factor (LIF), interleukin 11 (IL11), and heparin-binding EGF-like growth factor (HBEGF) mRNA, as well as secretion of LIF and IL11 protein. In order to mimic an inflammatory milieu as observed in active MS lesions, we combined FTY-P application with tumor necrosis factor (TNF). In the presence of this key inflammatory cytokine, FTY-P synergistically induced LIF, HBEGF, and IL11 mRNA, as well as secretion of LIF and IL11 protein. TNF itself induced inflammatory, B-cell promoting, and antiviral factors (CXCL10, BAFF, MX1, and OAS2). Their induction was blocked by FTY-P. After continuous exposure of cells to FTY-P or S1P for up to 7 days, the extent of induction of neurotrophic factors and the suppression of TNF-induced inflammatory genes declined but was still detectable. The induction of neurotrophic factors was mediated via surface S1P receptors 1 (S1PR1) and 3 (S1PR3). Conclusions We identified effects of FTY-P on astrocytes, namely induction of neurotrophic mediators (LIF, HBEGF, and IL11) and inhibition of TNF-induced inflammatory genes (CXCL10, BAFF, MX1, and OAS2). This supports the view that a part of the effects of fingolimod may be mediated via astrocytes