Automotive LiDAR sensors are seen by many as the enabling technology for higher-level autonomous driving functionalities. Different concepts to design such a sensor can be found in the industry. Some have already been integrated into consumer cars while many others promise to be in mass production soon to become cost-effective enough for broad deployment. However, automotive LiDAR sensors are still evolving and a variety of sensor designs are pursued by different companies. Here, we construct the automotive LiDAR design space to visually depict system design options for these sensors. Subsequently, we exemplify the concepts with drawings that can be found in published patent applications (focusing on scanning mechanisms and scan patterns) before discussing their advantages and challenges.
KEYWORDS: Laser stabilization, Field programmable gate arrays, Spectroscopy, Semiconductor lasers, Modulation, System on a chip, Rubidium, Photodiodes, Signal processing, Beam splitters, Frequency modulation, Digital signal processing
Frequency stabilized light sources with narrow linewidth are mandatory for atom interferometry based experiments. For compact experiment designs used on space platforms, tunable DFB diode lasers are often used. These lasers combine low energy consumption with small sizes, but lack long-term frequency stability. This paper presents an FPGA based laser frequency stabilization system for highly variable target frequencies using frequency modulated Rb-spectroscopy achieving latencies below 100 μs. The system consists of a DFB laser, a Rb-spectroscopy cell, a laser current controller and an FPGA board with an analog-digital conversion board. The digital part of the frequency stabilization system is a SoC mapped on an FPGA. The SoC consists of a processor, enabling user interaction via network connection, and the dedicated frequency stabilization module. This module consists of a demodulation stage, digital filters, a frequency estimator and a controller. To estimate the frequency, small ramps of the laser frequency are generated using a high-speed DAC connected to the laser current controller. The absorption spectroscopy output of this beam is sampled using a photodiode and a high-speed ADC. After signal conditioning with digital filters, the frequency estimator extracts the present mid-frequency of the laser applying pattern matching with a prerecorded reference spectrum. The frequency controller adjusts the mean laser current based on this estimation. The performance as well as the accuracy of the proposed laser stabilization system and its FPGA resource and power consumption are evaluated.
Motion estimation algorithms are a key component for multimedia systems and optimization of these algorithms is still a topic of current research. Promising approaches try to integrate into the motion estimation process besides pure grey level similarities further types of information, contained in the image. Due to the moderate quality of this additional information the integration has to be performed rather conservatively in order to reduce the risk of an even dramatic degradation of the vector field quality in some cases. Up to now there is no robust algorithm available, which yields a noticeable improvement for all types of motion and image scenes, without causing a loss of quality in critical situations.
Within the scope of this contribution the application of high performance segmentation for the enhancement of motion vector fields is analyzed. Starting from these results a new iterative concept for object based motion estimation is developed, which combines the results of a classic motion estimation with the information of image segmentation and features a high robustness against segmentation errors. The results of this new algorithm are analyzed on the basis of different objective evaluation criterions and compared to classic motion estimation algorithms.
One important task in the field of digital video signal processing is the conversion of one standard into another with different field and scan rates. Therefore a new vector-based nonlinear upconversion algorithm has been developed that applies nonlinear center weighted median filters (CWM). Assuming a two channel model of the human visual system with different spatio-temporal characteristics, there are contrary demands for the CWM filters. One can meet these demands by a vertical band separation and an application of so-called temporally and spatially dominated CWMs. By this means, interpolation errors of the separated channels can be compensated by an adequate splitting of the spectrum. Therefore a very robust vector error tolerant upconversion method can be achieved, which significantly improves the interpolation quality. By an appropriate choice of the CWM filter root structures, main picture elements are interpolated correctly even if faulty vector fields occur. To demonstrate the correctness of the deduced interpolation scheme, picture content is classified. These classes are distinguished by correct or incorrect vector assignment and correlated or noncorrelated picture content. The mode of operation of the new algorithm is portrayed for each class. Whereas the mode of operation for correlated picture content can be shown by object models, this is shown for noncorrelated picture content by the probability distribution function of the applied CWM filters. The new algorithm has been verified by objective evaluation methods [peak signal to noise ratio (PSNR), and subjective mean square error (SMSE) measurements] and by a comprehensive subjective test series.
Digital transmission of video signals and block-based coding/decoding schemes produce new artifacts such as blocking, dirty window, ringing and mosquite effects. These artifacts become worse with decreasing MPEG-2 data rates. Therefore the reduction of MPEG-artifacts becomes an attractive feature for digital TV-receivers. On the other hand an important feature for digital receivers is the performance of their postprocessing techniques such as object recognition, motion estimation, vector-based upconversion and noise reduction on MPEG-signals which are decoded in a receiver-based module called 'set top box'. In this paper different models dealing with the interaction between 'set top box' and digital receiver are discussed. Hereby the influence of MPEG-artifacts on postprocessing are presented. A vector-based upconversion algorithm which applied nonlinear center weighted median filters is presented. Assuming a 2-channel model of the human visual system with different spatio temporal characteristics, errors of the separated channels can be orthogonalized and avoided by an adequate splitting of the spectrum. Hereby a very robust vector error tolerant upconversion method which significantly improves the interpopulation quality is achieved. This paper describes also a concept for temporal recursive noise and MPEG-artifact filtering on TV images based on visual noise perception characteristics. Different procedures in the spatial subbands lead to results well matched to the requirements of the human visual system. Using a subband-based noise filter temporally non-correlated MPEG-artifacts can significantly be reduced. Image analysis using object recognition for video postprocessing becomes more important. Therefore a morphological, contour-based multilevel object recognition method which even stays robust in strongly corrupted MPEG-2 images is also introduced.
One important task in the field of digital video signal processing is the conversion of one standard into another with different field and scan rates. Therefore we have developed a vector based nonlinear upconversion algorithm which applies nonlinear center weighted median filters (CWM). Assuming a 2-channel model of the human visual system with different spatio temporal characteristics, there are contrary demands for the CWM filters. We can meet these demands by a vertical band separation and an application of so-called temporally and spatially dominated CWMs. Hereby errors of the separated channels can be orthogonalized and avoided by an adequate splitting of the spectrum. By this we have achieved a very robust vector error tolerant up-conversion method which significantly improves the interpolation quality. By an appropriate choice of the CWM filter root structures main picture elements are interpolated correctly also if faulty vector fields occur. In order to demonstrate correctness of the deduced interpolation scheme picture content is classified. These classes are distinguished by correct or incorrect vector assignment and correlated or noncorrelated picture content. The mode of operation of the new algorithm is portrayed for each class. Whereas the mode of operation for correlated picture content can be shown by object models this is shown for noncorrelated picture content by the distribution function of the applied CWM filters. The new algorithm has been verified as well by an objective evaluation method the PSNR (peak signal to noise ratio) measurement as by a comprehensive subjective test series.
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