Showing papers in "IEEE Transactions on Vehicular Technology in 2004"
TL;DR: The optimality and global convergence of the algorithm is proven and stopping criteria are given, and the global optimum of the downlink beamforming problem is equivalently obtained from solving a dual uplink problem, which has an easier-to-handle analytical structure.
Abstract: We address the problem of joint downlink beamforming in a power-controlled network, where independent data streams are to be transmitted from a multiantenna base station to several decentralized single-antenna terminals. The total transmit power is limited and channel information (possibly statistical) is available at the transmitter. The design goal: jointly adjust the beamformers and transmission powers according to individual SINR requirements. In this context, there are two closely related optimization problems. P1: maximize the jointly achievable SINR margin under a total power constraint. P2: minimize the total transmission power while satisfying a set of SINR constraints. In this paper, both problems are solved within a unified analytical framework. Problem P1 is solved by minimizing the maximal eigenvalue of an extended crosstalk matrix. The solution provides a necessary and sufficient condition for the feasibility of the SINR requirements. Problem P2 is a variation of problem P1. An important step in our analysis is to show that the global optimum of the downlink beamforming problem is equivalently obtained from solving a dual uplink problem, which has an easier-to-handle analytical structure. Then, we make use of the special structure of the extended crosstalk matrix to develop a rapidly converging iterative algorithm. The optimality and global convergence of the algorithm is proven and stopping criteria are given.
1,269 citations
TL;DR: A probabilistic model is developed to model human fatigue and to predict fatigue based on the visual cues obtained, and it was found to be reasonably robust, reliable, and accurate in fatigue characterization.
Abstract: This paper describes a real-time online prototype driver-fatigue monitor. It uses remotely located charge-coupled-device cameras equipped with active infrared illuminators to acquire video images of the driver. Various visual cues that typically characterize the level of alertness of a person are extracted in real time and systematically combined to infer the fatigue level of the driver. The visual cues employed characterize eyelid movement, gaze movement, head movement, and facial expression. A probabilistic model is developed to model human fatigue and to predict fatigue based on the visual cues obtained. The simultaneous use of multiple visual cues and their systematic combination yields a much more robust and accurate fatigue characterization than using a single visual cue. This system was validated under real-life fatigue conditions with human subjects of different ethnic backgrounds, genders, and ages; with/without glasses; and under different illumination conditions. It was found to be reasonably robust, reliable, and accurate in fatigue characterization.
749 citations
TL;DR: The goal of this paper is to propose an efficient tool to evaluate minimal fuel consumption that is achievable in simulation and based on optimal control theory, which can be easily applied to a large family of parallel arrangements.
Abstract: Control strategies for hybrid powertrains are algorithms that choose the power split between the engine and motor of a hybrid vehicle in order to minimize the fuel consumption and/or emissions. The goal of this paper is to propose an efficient tool to evaluate minimal fuel consumption that is achievable in simulation. Several approaches have been proposed, using heuristics (Delprat et al. 1999) or dynamic programming (Brahma et al., 2000; Rimaux et al., 1999). One drawback of these approaches is the huge amount of time required to obtain solutions. The approach described here is based on optimal control theory (Lewis & Syrmos, 1995) and avoids this drawback. Moreover, it can be easily applied to a large family of parallel arrangements.
461 citations
TL;DR: A novel set of orthogonal polynomials is introduced, which can be used for PA as well as predistorter modeling and generally yield better PA modeling accuracy as wellAs predistortion linearization performance.
Abstract: The polynomial model is commonly used in power amplifier (PA) modeling and predistorter design. However, the conventional polynomial model exhibits numerical instabilities when higher order terms are included. In this paper, we introduce a novel set of orthogonal polynomials, which can be used for PA as well as predistorter modeling. Theoretically, the conventional and orthogonal polynomial models are "equivalent" and, thus, should behave similarly. In practice, however, the two approaches can perform quite differently in the presence of finite precision processing. Simulation results show that the orthogonal polynomials can alleviate the numerical instability problem associated with the conventional polynomials and generally yield better PA modeling accuracy as well as predistortion linearization performance.
353 citations
TL;DR: A linearizing transform is used with a linear minimax approximation to determine an optimal lognormal approximation to a lognorian sum distribution, which is several orders of magnitude more accurate than previous approximations.
Abstract: Sums of lognormal random variables occur in many problems in wireless communications because signal shadowing is well modeled by the lognormal distribution. The lognormal sum distribution is not known in the closed form and is difficult to compute numerically. Several approximations to the distribution have been proposed and employed in applications. Some widely used approximations are based on the assumption that a lognormal sum is well approximated by a lognormal random variable. Here, a new paradigm for approximating lognormal sum distributions is presented. A linearizing transform is used with a linear minimax approximation to determine an optimal lognormal approximation to a lognormal sum distribution. The accuracies of the new method are quantitatively compared to the accuracies of some well-known approximations. In some practical cases, the optimal lognormal approximation is several orders of magnitude more accurate than previous approximations. Efficient numerical computation of the lognormal characteristic function is also considered.
314 citations
TL;DR: A previously proposed Kronecker-structure-based narrow-band model for nonline-of-sight (NLoS) indoor multiple-input-multiple-output (MIMO) radio channels based on 5.2-GHz indoor MIMO channel measurements is verified and it is shown that the MIMo channel covariance matrix can be well approximated by the Kr onecker product of the covariance matrices.
Abstract: In this paper, we first verify a previously proposed Kronecker-structure-based narrow-band model for nonline-of-sight (NLoS) indoor multiple-input-multiple-output (MIMO) radio channels based on 5.2-GHz indoor MIMO channel measurements. It is observed that, for the narrow-band case, the measured channel coefficients are complex Gaussian distributed and, consequently, we focus on a statistical description using the first- and second-order moments of MIMO radio channels. It is shown that the MIMO channel covariance matrix can be well approximated by the Kronecker product of the covariance matrices, seen from the transmitter and receiver, respectively. A narrow-band model for NLoS indoor MIMO channels is thus verified by these results. As for the wide-band case, it is observed that the average power-delay profile of each element of the channel impulse response matrix fits the exponential decay curve and that the Kronecker structure of the second-order moments can be extended to each channel tap. A wide-band MIMO channel model is then proposed, combining a simple COST 259 single-input-single-output channel model and the Kronecker structure. Monte Carlo simulations are used to generate indoor MIMO channel realizations according to the models discussed. The results are compared with the measured data using the channel capacity and good agreement is found.
266 citations
TL;DR: This paper proposes a new efficient collision resolution mechanism, called GDCF, based on the observation that 802.11 DCF decreases the contention window to the initial value after each success transmission, which essentially assumes that each successful transmission is an indication that the system is under low traffic loading.
Abstract: The medium-access control (MAC) protocol is one of the key components in wireless local area networks (WLANs). The main features of a MAC protocol are high throughput, good fairness, energy efficiency, and support priority guarantees, especially under distributed contention-based environment. Based on the current standardized IEEE 802.11 distributed coordination function (DCF) protocol, this paper proposes a new efficient collision resolution mechanism, called GDCF. Our main motivation is based on the observation that 802.11 DCF decreases the contention window to the initial value after each success transmission, which essentially assumes that each successful transmission is an indication that the system is under low traffic loading. GDCF takes a more conservative measure by halving the contention window size after c consecutive successful transmissions. This "gentle" decrease can reduce the collision probability, especially when the number of competing nodes is large. We compute the optimal value for c and the numerical results from both analysis and simulation demonstrate that GDCF significantly improve the performance of 802.11 DCF, including throughput, fairness, and energy efficiency. In addition, GDCF is flexible for supporting priority access by selecting different values of c for different traffic types and is very easy to implement it, as it does not requires any changes in control message structure and access procedures in DCF.
265 citations
TL;DR: This paper proposes a novel location technique that estimates the true, or line-of-sight (LoS), ranges based on NLoS range measurements, which utilizes a constrained nonlinear optimization approach, when range measurements are available from three base stations only.
Abstract: One of the main problems facing accurate location in wireless communication systems is nonline-of-sight (NLoS) propagation. In this paper, we propose a novel location technique that estimates the true, or line-of-sight (LoS), ranges based on NLoS range measurements. This approach utilizes a constrained nonlinear optimization approach, when range measurements are available from three base stations (BSs) only. Bounds on the NLoS error and the relationship between the true ranges are extracted from the geometry of the cell layout and the measured range circles to serve as constraints. Simulations studying the performance of the algorithm for different NLoS error distributions and BS configurations show that the location accuracy is significantly improved over traditional algorithms, even under highly NLoS conditions.
250 citations
TL;DR: This paper describes a method that uses a dynamic cell model and state-of-charge side information to very accurately predict the battery-pack available power.
Abstract: In some battery applications, such as in hybrid electric vehicles or battery electric vehicles, it is necessary to be able to estimate, in real time, the present available power that may be sourced by the battery pack. Similarly, in rechargeable packs, it may be necessary to know how much charging power the pack can accept. These values must be carefully calculated in such a way that the pack will not be damaged by over/under charge or voltage or by exceeding a design current or power limit. This paper describes a method that uses a dynamic cell model and state-of-charge side information to very accurately predict the battery-pack available power.
243 citations
TL;DR: The effects of gain, phase imbalance, and phase noise on EVM are examined on single-carrier, linear, and memoryless modulated signals, such as phase-shift keying and quadrature amplitude modulation (QAM).
Abstract: The error vector magnitude (EVM) is extensively applied as a measure of communication systems' performance. In this paper, the effects of gain, phase imbalance, and phase noise on EVM are examined. The work is focused on single-carrier, linear, and memoryless modulated signals, such as phase-shift keying and quadrature amplitude modulation (QAM). The EVM is calculated under the assumption that the transmitted signal consists of zero-mean uncorrelated inphase and quadrature components that are corrupted by additive white Gaussian noise. The contributions of this paper are as follows. First, an expression for the EVM is derived using a simple model that accounts for linear transmitter and receiver imperfections, inspired by the works of Cavers and Liao, 1993. Second, a union bound on the symbol error rate (SER) is derived. The root mean square EVM is shown to be independent of the constellation shape. The SER, however, is sensitive to the individual transmitted symbols and, therefore, the constellation shape. The resulting equations are used to examine the relation between EVM, sideband suppression, and phase noise.
241 citations
TL;DR: The simulation results indicate that ultracapacitors can more effectively assist the fuel cell to meet the vehicle power demand and help achieve a better performance and a higher fuel economy.
Abstract: This paper studies two hybrid power systems for vehicle applications: a fuel cell-battery hybrid powertrain and a fuel cell-ultracapacitor hybrid powertrain. First, the characteristics of fuel cell, battery, and ultracapacitor as power sources are summarized. Then the configurations of the two types of hybrid fuel cell powertrains are presented. Finally, example hybrid powertrains are designed and simulated using ADVISOR. The simulation results indicate that ultracapacitors can more effectively assist the fuel cell to meet the vehicle power demand and help achieve a better performance and a higher fuel economy.
TL;DR: This study shows that low hybridization levels provide an acceptable fuel economy benefit at a low price, while the optimal level of hybridization ranges between 0.3 and 0.5, depending on the total vehicle power.
Abstract: Hybrid electric vehicles have proved to be the most practical solution in reaching very high fuel economy as well as very low emissions. However, there is no standard solution for the optimal size or ratio of the internal combustion engine and the electric system. The optimum choice includes complex tradeoffs between the heat engine and electric propulsion system on one hand and cost, fuel economy, and performance on the other. Each component, as well as the overall system, have to be optimized to give optimal performance and durability at a low price. In this paper, we look at the effects of hybridization on fuel economy and dynamic performances of vehicles. Different hybridization levels from mild to full hybrid electric traction systems are examined. We also present the optimum level of hybridization for typical passenger cars. This study shows that low hybridization levels provide an acceptable fuel economy benefit at a low price, while the optimal level of hybridization ranges between 0.3 and 0.5, depending on the total vehicle power.
TL;DR: A probabilistic model for predicting traffic accidents using three-dimensional (3-D) model-based vehicle tracking is proposed and the effectiveness of the proposed algorithms is shown.
Abstract: Intelligent visual surveillance for road vehicles is the key to developing autonomous intelligent traffic systems. Recently, traffic incident detection employing computer vision and image processing has attracted much attention. In this paper, a probabilistic model for predicting traffic accidents using three-dimensional (3-D) model-based vehicle tracking is proposed. Sample data including motion trajectories are first obtained by 3-D model-based vehicle tracking. A fuzzy self-organizing neural network algorithm is then applied to learn activity patterns from the sample trajectories. Finally, vehicle activity is predicted by locating and matching each partial trajectory with the learned activity patterns, and the occurrence probability of a traffic accident is determined. Experiments show the effectiveness of the proposed algorithms.
TL;DR: The purpose of this paper is to introduce and justify the use of a new model for an energy source: a battery in parallel with an ultra-capacitor, to incorporate into hybrid electric vehicles to reduce their cost and increase the efficiency of their energy-source system.
Abstract: An energy source is the heart of a hybrid electric vehicle. If it is capable of supplying enough power at all times, then it is an adequate source. Major problems presently facing the industry include the size, cost, and efficiency of the energy source. The primary energy source presently used in automotive systems is a battery. In order to reduce the cost of the battery, the current needs to be decreased and stabilized so it is not very erratic. The purpose of this paper is to introduce and justify the use of a new model for an energy source: a battery in parallel with an ultra-capacitor. The ultra-capacitor can supply a large burst of current, but cannot store much energy. Conversely, the battery can store mass amounts of energy; however, without expensive and inefficient units, a battery cannot provide the current that the ultra-capacitor can. By combining the two energy sources in parallel, the storage and peak current characteristics desired can be achieved. The standards of the vehicle are not degraded, allowing this to be a promising technique to incorporate into hybrid electric vehicles to reduce their cost and increase the efficiency of their energy-source system.
TL;DR: The keyhole significantly degrades the SER performance of the STBC from idealistic behaviors in independent identically distributed MIMO channels, and the moment generating function (MGF) of instantaneous signal-to-noise ratio (SNR) after space-time block decoding (signal combining) in such channels is derived.
Abstract: In multiple-input-multiple-output (MIMO) fading environments, degenerate channel phenomena, called keyholes or pinholes, may exist under the realistic assumption that the spatial fading is uncorrelated at the transmitter and the receiver, but the channel has a rank-deficient transfer matrix. In this paper, we analyze the exact average symbol error rate (SER) of orthogonal space-time block codes (STBCs) with M-PSK and M-QAM constellations over Nakagami-m fading channels in the presence of the keyhole. We derive the moment generating function (MGF) of instantaneous signal-to-noise ratio (SNR) after space-time block decoding (signal combining) in such channels. Using a well-known MGF-based analysis approach, we express the average SER of the STBC in the form of single finite-range integrals whose integrand contains only the derived MGF. Numerical results show that the keyhole significantly degrades the SER performance of the STBC from idealistic behaviors in independent identically distributed MIMO channels.
TL;DR: Simulation results show the effectiveness of the proposed fault-tolerant control system for a high-performance induction motor drive that propels an electrical vehicle (EV) or hybrid electric vehicle (HEV).
Abstract: This paper describes a fault-tolerant control system for a high-performance induction motor drive that propels an electrical vehicle (EV) or hybrid electric vehicle (HEV). In the proposed control scheme, the developed system takes into account the controller transition smoothness in the event of sensor failure. Moreover, due to the EV or HEV requirements for sensorless operations, a practical sensorless control scheme is developed and used within the proposed fault-tolerant control system. This requires the presence of an adaptive flux observer. The speed estimator is based on the approximation of the magnetic characteristic slope of the induction motor to the mutual inductance value. Simulation results, in terms of speed and torque responses, show the effectiveness of the proposed approach.
TL;DR: The success of the MPC spacing-control laws is shown to depend on whether collision avoidance and the acceleration limits of the ACC vehicle are explicitly incorporated into the formulation of the control algorithm.
Abstract: In this paper, model predictive control (MPC) is used to compute the spacing-control laws for transitional maneuvers (TMs) of vehicles equipped with adaptive cruise control (ACC) systems. A TM is required, for example, to establish a steady-state following distance behind a newly encountered vehicle traveling with a slower velocity. These spacing-control laws are computed by formulating the objective of a TM as an optimal control problem (OCP). The steady-state following distance, collision avoidance, and acceleration limits of the ACC vehicle are incorporated into the OCP as constraints. The spacing-control laws are then obtained by solving this constrained OCP by using a receding-horizon approach, where the acceleration command computed at each sampling instant is a function of the current measurements of range and range rate. A baseline scenario requiring a TM is used to evaluate and compare the performance of the MPC algorithm and the standard constant time gap (CTG) algorithm. The simulation results show that the ACC vehicle is able to perform the TM of the baseline scenario using the MPC spacing-control laws, whereas the ACC vehicle is unable to perform this TM using the CTG spacing-control laws. The success of the MPC spacing-control laws is shown to depend on whether collision avoidance and the acceleration limits of the ACC vehicle are explicitly incorporated into the formulation of the control algorithm.
TL;DR: A novel two-dimensional (2-D) random-walk mobility model is proposed, which can be used for studying and analyzing the location-area crossing rate and dwell time of mobile users in wireless networks and has been extended to study an overlapped location- area strategy.
Abstract: In this work, a novel two-dimensional (2-D) random-walk mobility model is proposed, which can be used for studying and analyzing the location-area crossing rate and dwell time of mobile users in wireless networks. The development and application of the model under two cell structures, namely the square and hexagon cells, have been detailed. The analytical results obtained for location-update rates and dwell times have been validated using simulated and published results. The highlights of the model are its simplicity, minimal assumptions, and adaptability to conduct both "location-crossing rate" and "dwell-time" studies using the same model with slight modifications for either the square or hexagon cells. Using symmetry of mobile-user movement, a reduced number of computational states was achieved. A novel wrap-around feature of the model facilitates reduced assumptions on user mobility, which has also resulted in considerably reduced mathematical computation complexity. A regular Markov chain model was used for computing the average location-area crossing rate. A slightly modified model with absorbing states was used to derive the dwell time. This is the first model of its kind that can be used for studying area-crossing rates. To further emphasize the flexibility of the model, we have extended the model to study an overlapped location-area strategy. The study and analysis of overlapped locations areas has hitherto been difficult due to the complexity of the models.
TL;DR: This paper analyzes the symbol error rate (SER) performance of OFDM with M-ary phase-shift keying (M-PSK) modulation over Rayleigh-fading channels, in the presence of channel estimation errors.
Abstract: Orthogonal frequency division multiplexing (OFDM) with pilot symbol assisted channel estimation is a promising technique for high rate transmissions over wireless frequency-selective fading channels. In this paper, we analyze the symbol error rate (SER) performance of OFDM with M-ary phase-shift keying (M-PSK) modulation over Rayleigh-fading channels, in the presence of channel estimation errors. Both least-squares error (LSE) and minimum mean-square error (MMSE) channel estimators are considered. For prescribed power, our analysis not only yields exact SER formulas, but also quantifies the performance loss due to channel estimation errors. We also optimize the number of pilot symbols, the placement of pilot symbols, and the power allocation between pilot and information symbols, to minimize this loss, and thereby minimize SER. Simulations corroborate our SER performance analysis, and numerical results are presented to illustrate our optimal claims.
TL;DR: This paper investigates the effects of predicting the CSI using a linear fading-envelope predictor in order to enhance the performance of an ACM system and obtains approximative closed-form expressions for BER and average spectral efficiency.
Abstract: Adaptive coded modulation (ACM) is a promising tool for increasing the spectral efficiency of time-varying mobile channels while maintaining a predictable bit-error rate (BER). An important restriction in systems with such a transmission scheme is that the transmitter needs to have accurate channel-state information (CSI). Earlier analysis of ACM systems usually assumes that the transmitter has perfect knowledge of the channel or that the CSI is accurate but outdated. In this paper, we investigate the effects of predicting the CSI using a linear fading-envelope predictor in order to enhance the performance of an ACM system. For the case in which multidimensional trellis codes are used on Rayleigh-fading channels, we obtain approximative closed-form expressions for BER and average spectral efficiency. Numerical examples are given for the case of Jakes correlation profile and maximum a posteriori-optimal predictor coefficients.
TL;DR: A framework to analyze compact arrays for multiple-input-multiple-output (MIMO) is presented and different compact array configurations, which exploit spatial, polarization, and pattern diversity, are discussed and compared.
Abstract: A framework to analyze compact arrays for multiple-input-multiple-output (MIMO) is presented. Many handheld devices require very compact arrays. Small spacings between the antennas lead to mutual coupling, which decreases the efficiency of the antennas and therefor the signal-to-noise ratio and leads to correlated signals at the antennas. Both effects are completely taken into account in this framework; thus, it allows for a fair comparison of different antenna arrays for MIMO. It is distinguished between MIMO systems for multiplex transmission or pure beamforming, which have different requirements for the antennas. Different compact array configurations, which exploit spatial, polarization, and pattern diversity, are discussed and compared. For practical purposes, it is also shown how to connect this framework to standard path-based channel models.
TL;DR: A shape-independent pedestrian-detection system that needs only one pedestrian template-corresponding to a generic walking pose-and avoids brute-force searching for pedestrians throughout whole images, which typically involves brightness-similarity comparisons between candidate image patches and a multiplicity of pedestrian templates.
Abstract: Nighttime driving is more dangerous than daytime driving-particularly for senior drivers. Three to four times as many driving-related deaths occur at night than in the daytime. To improve the safety of night driving, automatic pedestrian detection based on infrared images has drawn increased attention because pedestrians tend to stand out more against the background in infrared images than they do in visible light images. Nevertheless, pedestrian detection in infrared images is by no means trivial-many of the known difficulties carry over from visible light images, such as image variability occasioned by pedestrians being in different poses. Typically, several different pedestrian templates have to be used in order to deal with a range of poses. Furthermore, pedestrian detection is difficult because of poor infrared image quality (low resolution, low contrast, few distinguishable feature points, little texture information, etc.) and misleading signals. To address these problems, this paper introduces a shape-independent pedestrian-detection method. Our segmentation algorithm first estimates pedestrians' horizontal locations through projection-based horizontal segmentation and then determines pedestrians' vertical locations through brightness/bodyline-based vertical segmentation. Our classification method defines multidimensional histogram-, inertia-, and contrast-based classification features. The features are shape-independent, complementary to one another, and capture the statistical similarities of image patches containing pedestrians with different poses. Thus, our pedestrian-detection system needs only one pedestrian template-corresponding to a generic walking pose-and avoids brute-force searching for pedestrians throughout whole images, which typically involves brightness-similarity comparisons between candidate image patches and a multiplicity of pedestrian templates. Our pedestrian-detection system is neither based on tracking nor does it depend on camera calibration to determine the relationship between an object's height and its vertical image locations. Thus, it is less restricted in applicability. Even if much work is still needed to bridge the gap between present pedestrian-detection performance and the high reliability required for real-world applications, our pedestrian-detection system is straightforward and provides encouraging results in improving speed, reliability, and simplicity.
TL;DR: Adaptive resource allocation for multimedia quality of service (QoS) support in broadband wireless networks is examined and an effective and efficient measurement-based dynamic resource allocation scheme is proposed to meet the target handoff-dropping probability.
Abstract: Adaptive resource allocation for multimedia quality of service (QoS) support in broadband wireless networks is examined in this work. A service model consisting of three service classes with different handoff-dropping requirements is presented. Appropriate call-admission control and resource-reservation schemes are developed to allocate resources adaptively to the real-time service classes with a stringent delay bound. Moreover, we propose an effective and efficient measurement-based dynamic resource allocation scheme to meet the target handoff-dropping probability. The nonreal-time applications, serviced by the best-effort model, are supported. The system accommodates adaptive multimedia applications to further reduce the blocking and dropping probabilities of real-time applications. Based on a multidimensional model analysis, simulations are conducted to evaluate the system performance. The simulation results show that the proposed system can satisfy the desired QoS of multimedia applications under different traffic loads, while achieving high utilization.
TL;DR: The proposed model is used to investigate various dual-polarization 2 /spl times/ 2 multiple-input-multiple-output (MIMO) schemes as well as to optimize the design of multipolarized MIMO schemes.
Abstract: This paper addresses the extension of a stochastic geometry-based scattering model to multipolarized transmissions. The initial approach is based on a geometrical distribution of obstacles derived from known power-delay profiles. Each scattering process is statistically described by a matrix reflection coefficient corresponding to dual-polarization states. Ultimately, the model allows us to simulate the effects of the range on K-factor, delay-spread, Doppler spectrum, channel correlations and capacity, branch power ratio, and cross-polar discrimination. Simulation results are compared with existing measurements at 2.5 GHz. The proposed model is then used to investigate various dual-polarization 2 /spl times/ 2 multiple-input-multiple-output (MIMO) schemes such as 0/spl deg//90/spl deg/ or /spl plusmn/45/spl deg/, as well as to optimize the design of multipolarized MIMO schemes.
TL;DR: A system for pedestrian detection in infrared images, which has been implemented on an experimental vehicle equipped with an infrared camera, based on a multiresolution localization of warm symmetrical objects with specific size and aspect ratio.
Abstract: This paper describes a system for pedestrian detection in infrared images, which has been implemented on an experimental vehicle equipped with an infrared camera. The proposed system has been tested in many situations and has proven to be efficient and with a very low false-positive rate. It is based on a multiresolution localization of warm symmetrical objects with specific size and aspect ratio; anyway, because road infrastructures and other road participants may also have such characteristics, a set of matched filters is included in order to reduce false detections. A final validation process, based on human shape's morphological characteristics, is used to build the list of pedestrian appearing in the scene. Neither temporal correlation nor motion cues are used in this first part of the project: the processing is based on the analysis of single frames only.
TL;DR: The benefit of including even-order nonlinear terms in baseband modeling of the PA and in enhancing predistortion performance is revealed.
Abstract: Power amplifier (PA) is an essential component in communication systems and is nonlinear in nature. Digital baseband predistortion is an emerging cost effective approach to linearize a PA. To study PA nonlinear characteristics and to construct a predistorter, accurate nonlinear models are often necessary. Polynomials have been used extensively for modeling the behavior of the PA or the predistorter. For bandpass communication signals, attention has been paid mainly to odd-order nonlinear terms. In this paper, we reveal the benefit of including even-order nonlinear terms in baseband modeling of the PA and in enhancing predistortion performance.
TL;DR: A geometric MIMO channel model is presented, which considers motion of the receiver and nonisotropic scattering at both ends of the radio link, and a joint space-time cross-correlation function is derived from this model and variates with this joint correlation are generated by using the vector autoregressive stochastic model.
Abstract: Wireless communication systems employing multiple antennas at both the transmitter and receiver have been shown to offer significant gains over single-antenna systems. Recent studies on the capacity of multiple-input-multiple-output (MIMO) channels have focused on the effect of spatial correlation. The joint effect of spatial and temporal correlation has not been well studied. In this paper, a geometric MIMO channel model is presented, which considers motion of the receiver and nonisotropic scattering at both ends of the radio link. A joint space-time cross-correlation function is derived from this model and variates with this joint correlation are generated by using the vector autoregressive stochastic model. The outage capacity of this channel is considered where the effects of antenna spacing, antenna array angle, degree of nonisotropic scattering, and receiver motion are investigated. When n transmit and n receive antennas are employed, it is shown that the outage capacity still increases linearly with respect to n, despite the presence of spatial and temporal correlation. Furthermore, analytical expressions are derived for the ergodic capacity of a MIMO channel for the cases of spatial correlation at one end and at both ends of the radio link. The latter case does not lend itself to numerical evaluation, but the former case is shown to be accurate by comparison with simulation results. The proposed analysis is very general, as it is based on the transmit and receive antenna correlations matrices.
TL;DR: The PSIM validity as an automotive simulation tool is discussed by creating module boxes for not only the electrical systems, but also the mechanical, energy-storage, and thermal systems of the vehicles.
Abstract: Automotive manufacturers have been taking advantage of simulation tools for modeling and analyzing various types of vehicles, such as conventional, electric, and hybrid electric vehicles. These simulation tools are of great assistance to engineers and researchers to reduce product-development cycle time, improve the quality of the design, and simplify the analysis without costly and time-consuming experiments. In this paper, a modeling tool that has been developed to study automotive systems using the power electronics simulator (PSIM) software is presented. PSIM was originally made for simulating power electronic converters and motor drives. This user-friendly simulation package is able to simulate electric/electronic circuits; however, it has no capability for simulating the entire system of an automobile. This paper discusses the PSIM validity as an automotive simulation tool by creating module boxes for not only the electrical systems, but also the mechanical, energy-storage, and thermal systems of the vehicles. These modules include internal combustion engines, fuel converters, transmissions, torque couplers, and batteries. Once these modules are made and stored in the library, the user can make the car model either a conventional, an electric, or a hybrid vehicle at will, just by dragging and dropping onto a schematic blank page.
TL;DR: It is shown that it is possible to design an unconditionally stable spacing policy, i.e., a spacing policy that guarantees traffic stability under all boundary conditions, and that the boundary conditions used at the inlets and exits influence traffic-flow stability in the case of the constant time-gap policy.
Abstract: This paper addresses the stability of traffic flow on a highway when the vehicles operate under an adaptive cruise-control (ACC) system. These systems are commonly designed to maintain a constant time gap between vehicles during vehicle following. Previous researchers in the literature have produced contradictory results on whether the traffic flow is stable when the constant time-gap spacing policy is used. This paper resolves the contradiction and shows that the boundary conditions used at the inlets and exits influence traffic-flow stability in the case of the constant time-gap policy. Further, this paper shows that it is possible to design an unconditionally stable spacing policy, i.e., a spacing policy that guarantees traffic stability under all boundary conditions. The practical implications of instability are shown through traffic-simulation results. The advantages of an unconditionally stable spacing policy over the constant time-gap policy are demonstrated. The answer to the question "Should ACC systems be designed to maintain a constant time gap between vehicles?" is "No" from a traffic-flow stability perspective. It is quite easy to develop alternate spacing policies with superior stability properties.
TL;DR: Diversity for dual-antenna systems operating in indoor environments is investigated and it is concluded from measurements at 900 MHz that antenna-pattern diversity is a better choice than space diversity for use at handhelds.
Abstract: This paper investigates diversity for dual-antenna systems operating in indoor environments. First, an approximated equation of the diversity gain is derived for different combining techniques. These theoretical results show that the two-term approximation, as generally used in the literature , is too rough an estimate. Consequently, a new six-term approximation is derived. Next, it is demonstrated by a comparison of theoretical and experimental diversity gain values that, due to mutual coupling between the two antennas in practice, the diversity gain will not approach 0 dB if the distance between the two antennas approaches zero. Finally, it is concluded from measurements at 900 MHz that antenna-pattern diversity is a better choice than space diversity for use at handhelds.