Spread-Doppler clutter caused by multi-mode propagation seriously affects the over-the-horizon radar detection performance for slow ships. To solve this problem, the authors propose to suppress multi-mode clutter usin...
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Spread-Doppler clutter caused by multi-mode propagation seriously affects the over-the-horizon radar detection performance for slow ships. To solve this problem, the authors propose to suppress multi-mode clutter using spatial information in the multiple-input-multiple-output over-the-horizon radar system. Traditional processing algorithms need prior information of the target direction. However, it is often not readily available. In this study, they propose a novel multi-mode clutter suppression algorithm based on the second-order blind identification (SOBI) technique. The proposed algorithm does not need prior information of the target direction and can effectively suppress the multi-mode clutter. Considering that the SOBI algorithm affected by the similarity in sources spectra, they improve the proposed algorithm using the spatial smoothing technique. Simulation results show that, in the single target scene, the improved algorithm can effectively eliminate the spectrum burrs caused by incomplete separation, making separated signals smoother. Signal-to-clutter-noise ratio is greatly improved. The good multi-mode clutter suppression performance is obtained. In the multi-mode scenario that double targets with the same radial velocity, that is, sources spectra have similarities, the algorithm based on SOBI cannot separate all targets. Although the improved algorithm can make all targets visible and effectively suppresses the multi-mode clutter.
By exploiting the direction of arrival (DoA) information of azimuth ambiguity, an innovative algorithm for the adaptive suppression of azimuth ambiguity for multichannel synthetic aperture radar (SAR) wide-swath imagi...
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By exploiting the direction of arrival (DoA) information of azimuth ambiguity, an innovative algorithm for the adaptive suppression of azimuth ambiguity for multichannel synthetic aperture radar (SAR) wide-swath imaging is presented. It firstly estimates the DoA value of each azimuth component within a Doppler cell using the efficient noise subspace-based iterative estimation technique. Then the spatial filter for sequentially extracting the desired azimuth component is derived, which is designed to be used with the newly estimated DoA information within each Doppler bin. Finally, the azimuth ambiguities can be suppressed via the implementation of spatial filtering. The proposed approach is robust to aircraft velocity errors, and its effectiveness is validated via simulation results.
One of the most exciting applications of V2X technologies, that is envisioned, is the platooning of a series of autonomous vehicles led by a manually driven vehicle. However, the realization of this application depend...
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ISBN:
(纸本)9781509018901
One of the most exciting applications of V2X technologies, that is envisioned, is the platooning of a series of autonomous vehicles led by a manually driven vehicle. However, the realization of this application depends entirely on the efficacy of a platoon control algorithm and the communication channel amongst the platoon members. There are many different control algorithms that are being considered to maintain a constant distance/time Gap amongst the platoon members based on the speed and acceleration profile of the other vehicles in the platoon. However, before a particular control algorithm can be deployed, it needs to be thoroughly analysed to see if it can indeed produce the desired effect under all sorts of traffic conditions and with varying penetration rates of V2X technology. In addition, one would also need to collect data on data packet delivery rate and the amount of delay, using different platoon management protocols. This information can then be utilized as a feedback to fine tune both the protocol and the control algorithm itself. This work aims to provide a holistic platform which integrates three simulators VISSIM (Traffic Simulation), NS-3 (Network Simulation) and MATLAB (Platoon control algorithm) that allows testing control algorithm stability in the presence of realistic communication constraints. To illustrate the usability of this co-simulation framework, we have presented results on velocity tracking of leader by follower vehicles while maintaining a specified inter-vehicular gap, for a small platoon along with results on data packet delivery for larger platoons.
One-class classification problem has been investigated thoroughly for past decades. Among one of the most effective neural network approaches for one-class classification, autoencoder has been successfully applied for...
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One-class classification problem has been investigated thoroughly for past decades. Among one of the most effective neural network approaches for one-class classification, autoencoder has been successfully applied for many applications. However, this classifier relies on traditional learning algorithms such as backpropagation to train the network, which is quite time-consuming. To tackle the slow learning speed in autoencoder neural network, we propose a simple and efficient one-class classifier based on extreme learning machine (ELM). The essence of ELM is that the hidden layer need not be tuned and the output weights can be analytically determined, which leads to much faster learning speed. The experimental evaluation conducted on several real-world benchmarks shows that the ELM based one-class classifier can learn hundreds of times faster than autoencoder and it is competitive over a variety of one-class classification methods.
Imperfect preventive maintenance (PM) activities are very common in industrial systems. For condition-based maintenance (CBM), it is necessary to model the failure likelihood of systems subject to imperfect PM activit...
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Imperfect preventive maintenance (PM) activities are very common in industrial systems. For condition-based maintenance (CBM), it is necessary to model the failure likelihood of systems subject to imperfect PM activities. In this paper, the models in the field of survival analysis are introduced into CBM. Namely, the generalized accelerated failure time (AFT) frailty model is investigated to model the failure likelihood of industrial systems. Further, on the basis of the traditional maximum likelihood (ML) estimation and expectation maximization (EM) algorithm, the hybrid ML-EM algorithm is investigated for the estimation of parameters. The hybrid iterative estimation procedure is analyzed in detail. In the evaluation experiment, the generated data of a typical degradation model are verified to be appropriate for the real industrial processes with imperfect PM activities. The estimates of the model parameters are calculated using the training data. Then, the performance of the model is analyzed through the prediction of remaining useful life (RUL) using the testing data. Finally, comparison between the results of the proposed model and the existing model verifies the effectiveness of the generalized AFT frailty model.
The nonlocal means algorithm is widely used in image denoising, but this algorithm does not work well for high-intensity noise. To overcome this shortcoming, we establish a coupled iterative nonlocal means model in th...
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The nonlocal means algorithm is widely used in image denoising, but this algorithm does not work well for high-intensity noise. To overcome this shortcoming, we establish a coupled iterative nonlocal means model in this paper. Considering the computation complexity of the new model, we realize it by using multiscale wavelet transform and propose an asymptotic nonlocal filtering algorithm which can reduce the influence of noise on similarity estimation and computation complexity. Moreover, we build a new nonlocal weight function based on the structure similarity index. Simulation results indicate that the proposed approach cannot only remove the noise but also preserve the structure of image and has good visual effects, especially for highly degenerated images.
This study proposes an algorithm for generating the associated Boolean expression in VHDL, given a ladder diagram (LD) as the input. The purpose of the algorithm is to implement of field-programmable gate array-(FPGA-...
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This study proposes an algorithm for generating the associated Boolean expression in VHDL, given a ladder diagram (LD) as the input. The purpose of the algorithm is to implement of field-programmable gate array-(FPGA-) based programmable logic controllers (PLCs), where an effective conversion from an LD to its associated Boolean expressions seems rarely mentioned. Based on this core thought, the conversion process of the algorithm first involves abstracting and expressing the encountered LD as an activity-on-vertex (AOV) graph. Next, an AND-OR tree in which AND-nodes and OR-nodes connote the series and the parallel relationships between the vertices of the AOV graph is constructed based on the AOV graph. Therefore, by a traversal to the AND-OR tree, the associated Boolean expression, as the output of the algorithm, can be easily obtained in VHDL. The proposed algorithm is then verified with an illustrative example, wherein a complicated LD is given as the input.
The area of metaheuristic optimization algorithms has been attracting researchers for many years. These algorithms have built in capability to explore a large region of the solution space, are computationally robust, ...
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The area of metaheuristic optimization algorithms has been attracting researchers for many years. These algorithms have built in capability to explore a large region of the solution space, are computationally robust, efficient and can avoid premature convergence. They have been extensively tested and applied on many hard optimization problems where conventional computing techniques perform unsatisfactorily. They are capable of solving general N-dimensional, linear, nonlinear and complex global optimization problems. One of the latest entrants in this field is the Bat algorithm which is based on the echolocation behaviour of bats. It has been proven to have good convergence properties on different benchmark functions and seems promising for dealing with optimization problems. The aim of this paper is to provide a survey of the state of the art on Bat algorithm. A concise effort has been made so that the readers get a rapid insight into some of the applications upon which bat algorithm has been applied till date in specialized fields of science and engineering. Some of the variants of the bat algorithm as reported in the literature have also been discussed.
Smart homes (SHs) are crucial parts for demand response management (DRM) of smart grid (SG). The aim of SHs based demand response (DR) is to provide a flexible two-way energy feedback whilst (or shortly after) the con...
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Smart homes (SHs) are crucial parts for demand response management (DRM) of smart grid (SG). The aim of SHs based demand response (DR) is to provide a flexible two-way energy feedback whilst (or shortly after) the consumption occurs. It can potentially persuade end-users to achieve energy saving and cooperate with the electricity producer or supplier to maintain balance between the electricity supply and demand through the method of peak shaving and valley filling. However, existing solutions are challenged by the lack of consideration between the wide application of fiber power cable to the home (FPCTTH) and related users' behaviors. Based on the new network infrastructure, the design and development of smart DR systems based on SHs are related with not only functionalities as security, convenience, and comfort, but also energy savings. A new multirouting protocol based on Kruskal's algorithm is designed for the reliability and safety of the SHs distribution network. The benefits of FPCTTH-based SHs are summarized at the end of the paper.
The large number of potential applications for robotic odor source localization has motivated the development of a variety of plume tracking algorithms, the majority of which work in restricted two-dimensional scenari...
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ISBN:
(纸本)9781509037636
The large number of potential applications for robotic odor source localization has motivated the development of a variety of plume tracking algorithms, the majority of which work in restricted two-dimensional scenarios. In this paper, we introduce a distributed algorithm for 3-D plume tracking using a system of ground and aerial robots in formation. We propose an algorithm that takes advantage of spatially distributed measurements to track the plume in 3-D and lead the robots to the source by integrating three behaviors - upwind movement, plume centering, and Laplacian feedback formation control. We evaluate this strategy in simulation and with real robots in a wind tunnel. For a source close to the ground, results show that a team of robots running our algorithm reaches the source with low lateral error while also tracing the horizontal and vertical plume shape.
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