Showing papers by "Saab Automobile AB published in 2020"

Radar Interference Mitigation for Automated Driving: Exploring Proactive Strategies

Abstract: Autonomous driving relies on a variety of sensors, especially radars, which have unique robustness under heavy rain/fog/snow and poor light conditions. With the rapid increase of the amount of radars used on modern vehicles, where most radars operate in the same frequency band, the risk of radar interference becomes a compelling issue. This article analyzes automotive radar interference and proposes several new approaches that combine industrial and academic expertise toward the goal of achieving interference-free autonomous driving (AD).

Safe management of bodies of deceased persons with suspected or confirmed COVID-19: a rapid systematic review.

Abstract: Introduction Proper strategies to minimise the risk of infection in individuals handling the bodies of deceased persons infected with 2019 novel coronavirus (2019-nCoV) are urgently needed. The objective of this study was to systematically review the literature to scope and assess the effects of specific strategies for the management of the bodies. Methods We searched five general, three Chinese and four coronavirus disease (COVID-19)–specific electronic databases. We searched registries of clinical trials, websites of governmental and other relevant organisations, reference lists of the included papers and relevant systematic reviews, and Epistemonikos for relevant systematic reviews. We included guidance documents providing practical advice on the handling of bodies of deceased persons with suspected or confirmed COVID-19. Then, we sought primary evidence of any study design reporting on the efficacy and safety of the identified strategies in coronaviruses. We included evidence relevant to contextual factors (ie, acceptability). A single reviewer extracted data using a pilot-tested form and graded the certainty of the evidence using the GRADE approach. A second reviewer verified the data and assessments. Results We identified one study proposing an uncommon strategy for autopsies for patients with severe acute respiratory syndrome. The study provided very low-certainty evidence that it reduced the risk of transmission. We identified 23 guidance documents providing practical advice on the steps of handling the bodies: preparation, packing, and others and advice related to both the handling of the dead bodies and the use of personal protective equipment by individuals handling them. We did not identify COVID-19 evidence relevant to any of these steps. Conclusion While a substantive number of guidance documents propose specific strategies, we identified no study providing direct evidence for the effects of any of those strategies. While this review highlights major research gaps, it allows interested entities to build their own guidance.

The COST IRACON Geometry-Based Stochastic Channel Model for Vehicle-to-Vehicle Communication in Intersections

Abstract: Vehicle-to-vehicle (V2V) wireless communications can improve traffic safety at road intersections and enable congestion avoidance. However, detailed knowledge about the wireless propagation channel is needed for the development and realistic assessment of V2V communication systems. We present a novel geometry-based stochastic MIMO channel model with support for frequencies in the band of 5.2–6.2 GHz. The model is based on extensive high-resolution measurements at different road intersections in the city of Berlin, Germany. We extend existing models, by including the effects of various obstructions, higher order interactions, and by introducing an angular gain function for the scatterers. Scatterer locations have been identified and mapped to measured multi-path trajectories using a measurement-based ray tracing method and a subsequent RANSAC algorithm. The developed model is parameterized, and using the measured propagation paths that have been mapped to scatterer locations, model parameters are estimated. The time variant power fading of individual multi-path components is found to be best modeled by a Gamma process with an exponential autocorrelation. The path coherence distance is estimated to be in the range of 0–2 m. The model is also validated against measurement data, showing that the developed model accurately captures the behavior of the measured channel gain, Doppler spread, and delay spread. This is also the case for intersections that have not been used when estimating model parameters.

A 0.6–4.0 GHz RF-Resampling Beamforming Receiver With Frequency-Scaling True-Time-Delays up to Three Carrier Cycles

Abstract: True-time-delays (TTDs) enable wideband analog and hybrid beamforming by mitigating the beam squint problem. This letter reports a TTD beamforming receiver supporting delays up to three carrier-frequency cycles. The implementation is the first published work in which the delays scale with the carrier frequency. The scaling enables TTDs for large arrays at low-GHz frequencies where long delays are required due to $\lambda _{c}/2$ antenna spacing. The delays are implemented through delayed resampling of a passive mixer’s discrete-time output. Driving the mixers with pulse-skipped local oscillator (LO) signals allows the delay range to exceed one carrier cycle. A polyphase receiver structure prevents aliasing of noise and unwanted tones caused by LO pulse-skipping. Our prototype implementation demonstrates squint-free beamforming for an-800 MHz instantaneous RF bandwidth. The proposed TTD is efficient for large arrays since the power consumption per antenna is only 5–13-mW across the 0.6–4.0-GHz frequency range. The prototype was implemented in 28-nm FD-SOI CMOS, and the die area including bonding pads is only 1.2 mm2.

A Statistical Analysis for Wavelength-Resolution SAR Image Stacks

Abstract: This letter presents a clutter statistical analysis for stacks of wavelength-resolution synthetic aperture radar (SAR) images. Each image stack consists of SAR images generated by the same sensor, using the same flight track illuminating the same scene but with a time separation between the illuminations. We test three candidate statistical distributions for time changes in the stack, namely, Rician, Rayleigh, and log-normal. The tests results reveal that the Rician distribution is a very good candidate for modeling stack of wavelength-resolution SAR images, where 98.59% of the tested samples passed the Anderson–Darling (AD) goodness-of-fit test. Also, it is observed that the presence of changes in the ground scene is related to the tested samples that have failed in the AD test for the Rician distribution hypothesis.

True-Time-Delay Beamforming Receiver With RF Re-Sampling

Abstract: Analog domain true-time-delays (TTD) are desired in hybrid beamforming receivers with large relative bandwidths to mitigate the problem of beam squint. We propose a true-time-delay beamforming receiver architecture which enables squint-free wideband spatial filtering prior to the A/D conversion. The receiver implements true-time-delay with delayed re-sampling of the discrete-time output of a passive mixer. The receiver has the capability to extend the range of the beamforming delays from one to several carrier periods of the RF signal with pulse-skipped local oscillator (LO) signals, thereby enabling TTD beamforming with large antenna arrays. Further, a polyphase structure with parallel mixers is proposed to prevent spectral aliasing resulting from the lowered sample rate of the pulse-skipped LO signals. In addition, the maximum beamforming delay scales with the LO frequency, supporting large arrays also at low frequencies where the antenna separation set by the wavelength is large. We verify the proposed concepts with transistor-level simulation of the receiver implemented with a 28-nm CMOS process. The design achieves a squint-free beamforming for a 400 MHz RF bandwidth, and a maximum beamforming delay of three carrier time periods. The power consumption for a 3 GHz carrier frequency is 4 mW per antenna.

GPS‐level accurate camera localization with HorizonNet

Abstract: This paper investigates the problem of position estimation of unmanned surface vessels (USVs) operating in coastal areas or in the archipelago. We propose a position estimation method where the hor ...

Wavelength-Resolution SAR Ground Scene Prediction Based on Image Stack.

Abstract: This paper presents five different statistical methods for ground scene prediction (GSP) in wavelength-resolution synthetic aperture radar (SAR) images. The GSP image can be used as a reference image in a change detection algorithm yielding a high probability of detection and low false alarm rate. The predictions are based on image stacks, which are composed of images from the same scene acquired at different instants with the same flight geometry. The considered methods for obtaining the ground scene prediction include (i) autoregressive models; (ii) trimmed mean; (iii) median; (iv) intensity mean; and (v) mean. It is expected that the predicted image presents the true ground scene without change and preserves the ground backscattering pattern. The study indicates that the the median method provided the most accurate representation of the true ground. To show the applicability of the GSP, a change detection algorithm was considered using the median ground scene as a reference image. As a result, the median method displayed the probability of detection of 97 % and a false alarm rate of 0 . 11 / km 2 , when considering military vehicles concealed in a forest.

Comparison of Automotive FMCW and OFDM Radar Under Interference

Abstract: Automotive radars are subject to interference in spectrally congested environments. To mitigate this interference, various waveforms have been proposed. We compare two waveforms (FMCW and OFDM) in terms of their radar performance and robustness to interference, under similar parameter settings. Our results indicate that under proper windowing both waveforms can achieve similar performance, but OFDM is more sensitive to interference.

Challenges in Using Neural Networks in Safety-Critical Applications

Abstract: In this paper, we discuss challenges when using neural networks (NNs) in safety-critical applications. We address the challenges one by one, with aviation safety in mind. We then introduce a possible implementation to overcome the challenges. Only a small portion of the solution has been implemented physically and much work is considered as future work. Our current understanding is that a real implementation in a safety-critical system would be extremely difficult. Firstly, to design the intended function of the NN, and secondly, designing monitors needed to achieve a deterministic and fail-safe behavior of the system. We conclude that only the most valuable implementations of NNs should be considered as meaningful to implement in safety-critical systems.

Design implications for teamwork in ATC

Abstract: In air trafc control (ATC), teamwork is a key component among air trafc control operators (ATCOs) to safely direct the aircraft through the sky and on the ground. To be able to design for future AT ...

Parametric investigation of low-dissipation low-dispersion schemes for unstructured flow solvers in large eddy simulation

Abstract: A second-order low-dissipation low-dispersion scheme is evaluated for unstructured finite-volume flow solvers. The scheme exploits a higher order central reconstruction of the face fluxes and a matrix dissipation formulation to reduce the dispersive and dissipative numerical errors. The scheme is applied using the M-Edge CFD solver for compressible flows for low-speed scale-resolving simulations. The scheme is shown to be a significant improvement to a conventional central scheme used for RANS simulations by accurately predicting reference DNS data for the plane channel flow and experimental data for the decaying homogenous isotropic turbulence.

Multiple Access Radar Using Slow Chirp Modulation

Abstract: The cohabitation of several radars, operating in the same frequency band, has become an essential and urgent topic as active safety systems for automotive applications are rolled out. An obvious concern is that mutual interference must be managed. Separating users in time, i.e. TDMA, achieves the required level of isolation in a straightforward way. CDMA techniques providing sufficient channel isolation are less obvious. The paper develops an alternative CDMA method, called Slow Chirp Modulation (SCM). SCM utilizes the full coherent integration time for transmission of a single aperiodic but ergodic signal, allowing target range and velocity to be retrieved but minimizing spectral occupancy. Spectral efficiency two orders of magnitude higher than for the discussed alternative methods is obtained, allowing more than a thousand non-interfering channels. Relying on indicated hardware schematics, the paper demonstrates the functionality of the novel signal processing algorithms, which are required for SCM.

“PREParE SHIPS” for Automated Ship Passages by Modern Decision Support Tools by Exchanging Future Positions

Abstract: Misunderstanding the intentions of other vessels is one of the most common causes of ship collisions today. Such misunderstandings are particularly dangerous during navigation in restricted areas, such as fairways, port areas, and inland water ways, and may be exacerbated with the introduction of unmanned vessels. To ensure safe operations, the understanding of the intentions and future positions of manned and unmanned vessels, the PREParE SHIPS project is creating a system capable of determining a ship's position with high accuracy, predicting its future positions, and communicating the current and future positions. The positioning sub-system combines the signals of Galileo and EGNOS, EGNSS and SBAS respectively, with land based RTK corrections, providing a positioning accuracy of centimetres. Furthermore, by taking advantage of Galileo's authentication features, the positioning system provides enhanced security measures against spoofing attacks. The prediction sub-system will use a ship dynamic model and machine learning to predict the future positions of the ship and improve said predictions with time, while the communication sub-system will broadcast the prediction through VDES ship2ship and ship2shore. PREParE SHIPS will improve the navigation and handling of ships, through high accuracy positioning and dynamic predictions, as well as reduce the risk of ship collisions, through the communication of present and predicted future positions. PREParE SHIPS is expected to increase safety and efficiency significantly and will be the base of future autonomous operations and standardisations.

Support pole and stake for net support system

Abstract: A net support system for supporting a net may include a support pole configured to hold up a net, one or more stakes configured to hold the net to a ground surface; and a shape disrupter configured to interface with the support pole and to hold up the net The support pole and each of the one or more stakes are non-metallic, non-conductive, and radar transparent Each of the one or more stakes may have a central rib A storage case may be provided for storing the plurality of shape disrupters, the plurality of support poles, and the plurality of stakes

Exploring the sensor requirements for particle filter-based terrain-aided navigation in AUVs

Abstract: One of the main challenges faced by autonomous underwater vehicles (AUVs) is their navigation capability. A commonly used navigation strategy is dead-reckoning inertial navigation integrated with a seafloor-tracking Doppler velocity log (DVL). The disadvantage with this technique is the un-bounded accumulation of errors during operation. Terrain-aided navigation (TAN) has been deemed as a viable approach to compensate for dead-reckoning navigation errors. This type of navigation uses a predefined map of the seafloor and estimates the position of the vehicle on the map by matching the map to bathymetry measurements from vehicle sensors.The physical limitations of an AUV platform places restrictions on what kind of sensors can be used, such as weight, size, resolution, power consumption and accuracy. For this reason, a dedicated TAN-sensor is undesirable. In addition to a DVL, many vehicles make use of a forward-looking sonar (FLS) for obstacle avoidance. In this work, we implement a particle filter-based TAN algorithm using DVL altitude data fused with FLS information. We simulate TAN navigation for several different types of FLS, and compare the navigation performance. In general, we find that navigation performance improves with the number of sonar beams. This is expected, as a more complex sensor means more information is gathered and input to the navigation. However, we also find that a configuration using just three single-beam echo sounders performs as well as a proper multibeam FLS.The results show that the multiple single-beam echo sounder configuration is an interesting solution due to its high accuracy during the navigation while retaining a low impact on the platform dynamics and power consumption.