Comparison of matching layers for automotive radome design

Hidden integration of 79 GHz sensors behind plastic and painted fascia represents a challenging task since both electromagnetic and car body design constraints have to be met. This paper compares different possibilities for low-cost integration of radar sensors. Based on a model for stratified media, a study of the most important parameters such as bandwidth, angle and tolerances is shown. Our results suggest that for plastic fascia, the requirements of future radar sensors can be met with low-cost matching. Even with metallic paints, the requirements imposed by modern 79 GHz radar sensors can be met under certain conditions

Pedestrian recognition using automotive radar sensors

The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects

Statistical sensor fusion of ECG data using automotive-grade sensors

Driver states such as fatigue, stress, aggression, distraction or even medical emergencies continue to be yield to severe mistakes in driving and promote accidents. A pathway towards improving driver state assessment can be found in psycho-physiological measures to directly quantify the driver's state from physiological recordings. Although heart rate is a well-established physiological variable that reflects cognitive stress, obtaining heart rate contactless and reliably is a challenging task in an automotive environment. Our aim was to investigate, how sensory fusion of two automotive grade sensors would influence the accuracy of automatic classification of cognitive stress levels. We induced cognitive stress in subjects and estimated levels from their heart rate signals, acquired from automotive ready ECG sensors. Using signal quality indices and Kalman filters, we were able to decrease Root Mean Squared Error (RMSE) of heart rate recordings by 10 beats per minute. We then trained a neural network to classify the cognitive workload state of subjects from heart rate and compared classification performance for ground truth, the individual sensors and the fused heart rate signal. We obtained an increase of 5 % higher correct classification by fusing signals as compared to individual sensors, staying only 4 % below the maximally possible classification accuracy from ground truth. These results are a first step towards real world applications of psycho-physiological measurements in vehicle settings. Future implementations of driver state modeling will be able to draw from a larger pool of data sources, such as additional physiological values or vehicle related data, which can be expected to drive classification to significantly higher values

Optimized tracking for cooperative sensor systems in multipath environments

In a cooperative sensor system for pedestrian protection, a pedestrian and other road users exchange data by means of radio frequency communication. In the proposed system, the pedestrian carries a transponder which is interrogated by a vehicle and sends an anonymous identification (ID) sequence. By decoding the ID, the interrogation unit in the vehicle detects the presence of the transponder. Evaluating the incident wave of the transponder's answer, a localisation is possible. <br><br> In the proposed localization system, the measurement results can be distorted by multipath propagation. Multipath errors result if signals of the same transponder arrive simultaneously at the receiver unit from different directions. In this case, erroneous distances and angles are measured. Because the signals arriving from different directions contain the same transponder ID, they can be assigned to their origin. One of the challenges in post-processing for signal improvement is enhancing the selection of the correct position information by making assumptions about the pedestrian's movement and by knowing the vehicle's current driving parameters. Additionally, information contained in multipath signals is used to form a better estimate for the true position of the transponder. To overcome the problems related to multipath propagation effects, a method is proposed that estimates the origin of a multipath signal and maps the distorted position information back to the true position. A fusion of tracked direct positions and mapped multipath signals leads to an improvement in positioning accuracy

Experimental models of Hepatitis D virus infection

Papers presented at the International conference on Hepatitis BAvailable from Centro de Informacion y Documentacion Cientifica CINDOC. Joaquin Costa, 22. 28002 Madrid. SPAIN / CINDOC - Centro de Informaciòn y Documentaciòn CientìficaSIGLEESSpai

Antennensystem, Sichtscheibe und Kraftfahrzeug

DE 102008027371 A1 UPAB: 20091216 NOVELTY - The antenna system (12) for a motor vehicle (10) includes a surface arrangement of flat antenna elements (16) on a dielectric carrier and an electrically conductive Faure plate (18) on the opposite surface to the carrier. The dielectric carrier is in the form of one or more layers of the laminar windscreen (14) of the vehicle. There is an arrangement of several holes in the Faure plate. USE - For a motor vehicle. ADVANTAGE - Enables advantages of planar or micro-strip antenna to be applicable to a motor vehicle

Virtual sensor models for real-time applications

Increased complexity and severity of future driver assistance systems demand extensive testing and validation. As supplement to road tests, driving simulations offer various benefits. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensor-model, is described. The state-space based method is capable of modeling various types behavior. In this contribution, the modeling of the position estimation of an automotive radar system, including autocorrelations, is presented. For rendering real-time capability, an efficient implementation is presented