The transition to connected vehicles (CVs) is shaping the future of autonomous and highly connected vehicles. As the vehicles’ reliance on increasingly complex software increases, more central points of failure are introduced. This necessitates more thorough and scalable anomaly and intrusion detection systems. Conventional approaches can struggle with the complex and dynamic structures of CVs while not providing any automatic response actions. Therefore, machine learning-based anomaly detection methods are gaining popularity. Reinforcement Learning especially has shown the potential to increase configurability and provide end-to-end solutions. Thus, this paper presents a Systematic Literature Review (SLR) on Reinforcement Learning (RL) for anomaly and intrusion detection, applicable for CVs. In it, different RL algorithms and the analysis of how they can be used for training and detecting anomalies are presented. The problem formulations for different approaches are compared, their advantages and challenges are discussed. Additionally, the potential of using RL to react to anomalies is presented, discussed and advocated for. The results of the survey indicate that many of the identified RL formulations are not inherently superior from supervised learning approaches. However, RL techniques can result in better configurability of anomaly detection system, enabling site reliability engineers to efficiently adjust the model via reward functions. Furthermore, it becomes evident that the strengths of RL-based anomaly detection are best leveraged when used for reacting to anomalies. Therefore, the authors propose to focus on the contextual or sequential decision making formulation including corrective actions, compared to the classification-based detection formulations using RL.

The rise of software-defined automation systems is accompanied by an increase in interconnected services and networks. Among other implications, this leads to an expansion of the attack surface for cyber threats, which in turn can lead to significant security issues and financial losses. Against this background, this paper investigates the effectiveness of anomaly-based intrusion detection systems (IDS) for detecting and preventing new and evolving cyber threats. The paper especially considers the challenge of concept drift, which describes the phenomenon that the statistical properties of the network traffic or behavior patterns that an IDS is trying to detect change over time. To accomplish this, a comprehensive literature review, prioritizing recent studies since 2019, highlights the challenges of concept drift and the application of reinforcement learning in IDS. The results suggest that the integration of adaptive strategies and reinforcement learning in IDS enables significant improvements in anomaly detection.

As software-defined vehicles continue to dominate automotive research, the vision for a future of extensively connected vehicular environments, including vehicle-to-everything (V2X) communications and nationwide connected infrastructures, grows more pronounced. However, despite the existence of standards to support these advances, widespread adoption and integration into broader vehicular ecosystems remain elusive.Thus, the scope of this paper is to explore potential connected vehicle functions of the future and outline potential paths toward their realization. Utilizing the Delphi method, the authors engaged with experts from the German automotive industry to gain insights into emerging and feasible connected vehicle functions. The interviews served as a primary source for identifying promising vehicle functions, which were subsequently compared against existing literature to detect related functions and to group them into coherent clusters. Finally, by combining these clusters and the acquired knowledge, visions for the future of mobility were derived.The findings of this study reveal that the trajectory toward implementing connected vehicle functions is unlikely to follow a linear path. Instead, development is expected to occur through multiple, parallel scenarios. The success and prevalence of specific use cases will largely depend on the development of viable monetization strategies and business models that can sustain these individual "islands" of innovation. The paper concludes that future research should focus on strategies to integrate these disparate islands, aiming to forge a unified and comprehensive vehicular communication system.

An increasing proportion of software characterizes modern automated systems such as vehicles. It can be used to provide new functions to improve the customer experience in terms of automation, personalization, and connectivity. For system development, this means that classic processes must be rethought and supplemented by new strategies. This is mapped via the trend of the software-defined systems. In this context, individual components can be improved over the entire life cycle. In order for these updates to function properly, testing before deployment is commonplace. However, since the software is complex and it is infeasible to test 100% of the possible scenarios, a software update can still lead to unforeseen side effects. At the same time, it must be monitored whether the desired update effects actually apply. In the worst case, the side effects include errors that must be found as quickly as possible in order not to negatively influence product quality and subsequent innovation cycles. The goal of this work is to detect side effects that manifest themselves as anomalies at runtime and to trace them back to the corresponding code change. For this purpose, a new approach is presented that uses the digital twin of the vehicle as an information base, providing operational data and simulations parallel to operation. The simulation generates synthetic data also containing the rare and risky cases that can then be matched against the operational data to identify anomalies. Once an anomaly is detected, a subsequent analysis follows that relates the anomaly to a causal code sequence. The presented approach is realized using the example of a model vehicle with microcontrollers and corresponding peripherals such as sensors and motors. The model vehicle is simulated using the simulation software SimulIDE, which provides the synthetic data. The evaluation shows that the trace back of side effects to the respective code sequences can successfully be achieved.

Today’s systems engineering is challenged by an increasing number of requirements aimed at smaller target audiences. This leads to a rise of variants to fulfill individual consumer demands. Because of the complexity introduced by the surge of software-defined mechatronic systems, deriving new variants manually is becoming increasingly difficult. As of today, however, there exist no well-established methods or tools to assist in variant generation. This article aims to fill this gap by presenting a novel approach that enables an automated, requirements-based variant generation. For this purpose, a variant meta-model capable of both storing and interconnecting physical parameters and qualitative criteria of system components is designed and translated into a machine-readable form. The resulting data model is described to be stored inside a multi-model database, allowing for the integration of past project data by using data mining techniques. Additionally, a variant generation algorithm with a strategy for targeted exploration of the variant solution space is presented. The complete approach is realized by implementing a demo application that includes both the multi-model database and a java application for algorithm execution. Our work is evaluated by benchmarks using a dataset with real-world components, indicating that requirements-conform variants can be generated in a reasonable time.

Nowadays, formal methods are used in various areas for the verification of programs or for code generation from models in order to increase the quality of software and to reduce costs. However, there are still fields in which formal methods haven’t been widely adopted, despite the large set of possible benefits offered. This is the case for the area of programmable logic controllers (PLC). This article aims to evaluate the potential of formal methods in the context of PLC development. For this purpose, the general concepts of formal methods are first introduced and then transferred to the PLC area, resulting in an engineering-oriented description of the technology that is based on common concepts from PLC development. Based on this description, PLC professionals with varying degrees of experience were interviewed for their perspective on the topic and to identify possible use cases within the PLC domain. The survey results indicate the technology’s high potential in the PLC area, either as a tool to directly support the developer or as a key element within a model-based systems engineering toolchain. The evaluation of the survey results is performed with the aid of a demo application that communicates with the Totally Integrated Automation Portal from Siemens and generates programs via Fastsynth, a model-based open source code generator. Benchmarks based on an industry-related PLC project show satisfactory synthesis times and a successful integration into the workflow of a PLC developer.

Sparse Representation and Compressive Sensing (CS) theory has gained an increasing interest during the last years in many application fields, including SAR tomography. The latter offers the possibility to perform a focusing, beyond the classical 2D (azimuth-range) domain, along other dimensions: f.i., elevation and velocity. The literature, however, lacks of an assessment of the improvement of CS over classical point cloud detection schemes based on the Generalized Likelihood Ratio test which, in the simplest form, use basic beamforming (matched filter) detection based schemes. This work aims to provide a contribution along this line.

The papers in this special issue cover the most topical research areas in Synthetic Aperture Radar (SAR) techniques and technologies as bistatic SAR, innovative system concepts, polarimetric systems and data analysis, polarimetric SAR interferometry, as well as advanced processing techniques for image generation and information extraction.

Using coarse-grained membrane simulations we show here that peripheral membrane proteins can form a multitude of higher-order structures due to membrane-mediated interactions. Peripheral membrane proteins characteristically perturb the lipid bilayer in their vicinity which supports the formation of protein assemblies not only within the same but surprisingly also across opposing leaflets of a bilayer. In addition, we also observed the formation of lipid-protein domains on heteregeneous membranes. The clustering ability of proteins, as quantified via the potential of mean force, is enhanced when radius and hydrophobic penetration depth of the proteins increases. Based on our data, we propose that membrane-mediated cluster formation of peripheral proteins supports protein assembly in vivo and hence may play a pivotal role in the formation of templates for signaling cascades and in the emergence of transport intermediates in the secretory pathway.

The 29 papers in this special issue cover the most topical research areas in SAR techniques and technologies, such as bistatic SAR, innovative system concepts, polarimetric systems and data analysis, polarimetric SAR interferometry, and advanced processing techniques for image generation and information extraction.

This paper summarizes a special session on multi-core/multi-processor system-on-chip (MPSoC) programming challenges. Wireless multimedia terminals are among the key drivers for MPSoC platform evolution. Heterogeneous multi-processor architectures achieve high performance and can lead to a significant reduction in energy consumption for this class of applications. However, just designing energy efficient hardware is not enough. Programming models and tools for efficient MPSoC programming are equally important to ensure optimum platform utilization. Unfortunately, this discipline is still in its infancy, which endangers the return on investment for MPSoC architecture designs. On one hand there is a need for maintaining and gradually porting a large amount of legacy code to MPSoCs. On the other hand, special C language extensions for parallel programming as well as adapted process network programming models provide a great opportunity to completely rethink the traditional sequential programming paradigm for sake of higher efficiency and productivity. MPSoC programming is more than just code parallelisation, though. Besides energy efficiency, limited and specialized processing resources, and real-time constraints also growing software complexity and mapping of simultaneous applications need to be taken into account. We analyze the programming methodology requirements for heterogeneous MPSoC platforms and outline new approaches.

The interest in bi- and multistatic radar has been growing over the last years as they offer various advantages. For instance the transmitter and receiver can easily be separated and therefore the survivability can be enhanced by deploying the transmitter further away from the scene. Bistatic radar can provide a cost effective solution as the transmitter and receiver can be built without the cost driving transmit/receive-modules. Beyond this, with large baselines it is likely to increase the signature from stealthy objects. Another interesting aspect of bistatic imaging radar is the reduced dynamic range of difficult imaging environments such as urban ones. However, besides the benefits of bi- and multistatic radar one has to solve several technical problems [1] - such as the synchronisation and determining the relative position and orientation of both platforms towards each other. This paper discusses a method which allows determining these two fundamental parameters of an airborne bistatic SAR system and presents first simulations result, which confirms the method.

Applications of small unmanned aerial vehicles (UAV) have increased steadily over the past years. Applications are found in earth observation, reconnaissance, monitoring, and surveillance missions using imaging systems. The big advantage of radar sensors is their all-weather capability. Especially imaging radars possess several benefits over optical systems, as they are not affected by rain, snow, fog, or the time of day. The advantages using small unmanned platforms come at the cost of having to deal with restrictions on weight and volume. Hence, these parameters are the predominant design drivers for UAV sensor developments. This paper presents the concept, the technical realization and the status of a 3D imaging radar system suitable for small UAVs. ARTINO (Airborne Radar for Three dimensional Imaging and Nadir Observation) combines a real aperture, realized by a linear array of nadir pointing antennas, and a synthetic aperture, which is spanned by the moving airplane.

Following the goals of our cooperation treaty between FGAN and ZESS (University Siegen), we work closely together on the complex research field of bistatic exploration. Single tasks of the overall topic are for instance experimental missions, processing, image formation, position- and attitude estimation, synchronisation, simulation, parameter estimation, and visualization. This paper presents an overview about the common projects of FGAN, ZESS, and FOMAAS.

Bistatic radar is gaining more and more interest over the last years. It offers more freedom to deploy the transmitter and the receiver, e.g. in a way to enhance the signature of stealthy targets. Furthermore, the bi- or multistatic system can be realized without using expensive transmit/receive-modules. An additional feature of bistatic radar is that continuous wave signals can be used. A crucial problem associated with bi- and multistatic systems is the synchronisation of time and frequency at the transmitters and receivers for coherent signal processing and range measurement. Modern communications satellites and world wide accessible GPS signals allow to synchronise the time easily over a long period with a time difference of less than 1 ns. The required frequency stability depends on the baseline and may vary with application. Image generation with bistatic SAR systems requires a frequency coherence for at least the coherent integration time. For interferometric SAR systems this coherence has to be expanded over the whole processing time. The paper concentrates on the problem of time and frequency synchronisation between a bistatic transmitter and receiver pair. Possible solutions for attaining the requirements of bistatic radar systems are discussed.

This paper describes the concept and reports the status of the FGAN Experimental Bistatic Radar (EBiRa). The main field of this bistatic radar investigation is air surveillance operation with host off ground-based cooperative illuminators. Also possible is the use of noncooperative illuminators like FM radio stations, TV stations, or monostatic radars which are located in the observation area. The receiver and transmitter are build up with commercial-off-the-shelf components to reduce cost and shorten the development time. New digital signal generation and processing technologies came into operation for both units.

A high resolution synthetic aperture radar (SAR) system called phased array multifunctional imaging radar (PAMIR) is currently under development at FGAN. This system uses a very high bandwidth and performs a coherent integration along a large synthetic aperture. Problems in the area of calibration and motion compensation arise which can't be solved using common tools like corner reflectors. This paper describes the construction of active transponders which modulate and re-radiate radar pulses, discusses the advantages for calibration and shows how the echoes can be used for motion compensation in the SAR processing.

In this paper, we provide an overview of the hardware-software design flow that has been applied to the design of a platform based SoC for the HiperLAN/2 and IEEE 802.11a wideband wireless communication standards. Starting from a high-level description in MATLAB, the design framework is used to gain important information for the HW/SW partitioning. Step by step the MATLAB description is refined down to an embedded assembler implementation. Simultaneously, the framework is used to generate cycle true reference data for simulations on several abstraction levels. A universal interface concept allows the exchange of modules of different abstraction levels in a cosimulation. This way, a high confidence level for the design verification is achieved, and design and verification time is substantially reduced.

We provide an overview of a MATLAB/sup TM/ based hardware-software design flow that has been applied to the design of a platform based SoC for the HiperLAN/2 and IEEE 802.11 wideband wireless communication standards. Starting from a high-level algorithmic description, the MATLAB/sup TM/ environment serves as a "golden model" and universal, cycle-true testbench for the embedded hardware and software implementation. A universal interface concept allows the exchange of modules with different abstraction levels in a cosimulation. This way, a high confidence level for the design validation is achieved, and both design and validation time is substantially reduced.

The ongoing advances in semiconductor technology are the enabler for complete system on chip (SoC) solutions. In this SoC domain digital signal processors (DSPs) are employed to carry out software driven digital signal processing tasks. Although DSPs could still be modified in the SoC domain, they are mainly employed as fixed DSP cores. Possible adaptations to the embedding system cannot be carried out. Thus, our work is targeted to design expandable DSP architectures. To achieve this expandability, we designed a sliced DSP architecture. Here, the number of slices can be adapted towards the system's needs. Specific system requirements can be achieved by adding dedicated datapaths to these slices. With this approach one magnitude of order in performance boost can be achieved, which creates new demands for I/O processing. Thus, within our DSP architecture we integrated a dedicated I/O processor. We present this new scalable DSP architecture, tools to map algorithms onto this DSP architecture, and the concept of our new I/O controller. These technologies allow one to easily adapt this DSP architecture to different system requirements.

Performance enhanced DSP (digital signal processor) architectures incorporate either datapath add-ons such as dual-MAC architectures or tailored datapaths such as Viterbi accelerators. Both strategies strongly influence the instruction set architecture (ISA). Since common ISAs are not designed for architectural enhancements, either a complete redesign is required or architectural enhancements cannot be fully exploited by the ISA. Taking the GSM fullrate vocoder as an example, a structural approach is presented to show how datapath add-ons or tailorizations can be applied to increase the DSP's performance. To efficiently utilize architectural enhancements we propose a modified VLIW (very long instruction word) ISA, called TVLIW (tagged VLIW). TVLIW combines both VLIW performance and DSP codewidth requirements. To demonstrate the applicability, we applied the TVLIW ISA to a highly pipelined quadruple-MAC architecture, incorporating only one dualport RAM and a 26-bit wide instruction word.