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Horizontal wind velocity retrieval using a Levenberg-Marquardt algorithm for an airborne wind lidar

JOURNAL OF APPLIED REMOTE SENSING 2016年第2期10卷 026009-1-026009-10页

作者： Zhu, Jinshan Li, Zhigang Liu, Zhishen Shandong Univ Sci & Technol Coll Geomat 579 Qianwangang Rd Qingdao 266590 Peoples R China Natl Adm Surveying Mapping & Geoinformat China Key Lab Surveying & Mapping Technol Isl & Reef 579 Qianwangang Rd Qingdao 266590 Peoples R China Ludong Univ Sch Phys & Optoelect Engn 186 Middle Hongqi Rd Yantai 264025 Peoples R China Ocean Univ China Ocean Remote Sensing Inst 5 Yushan Rd Qingdao 266003 Peoples R China

We established a model for an airborne wind lidar. Numerical optimization algorithms should be used to solve this nonlinear model. We designed a Levenberg-Marquardt (L-M) algorithm and tested it with the modeled data. The retrieved velocity and the true velocity agree very well, and the adjusted R-2 is 0.99947. We have carried out an airborne coherent wind lidar experiment in January 2015, and we used the model and the L-M algorithm to process the wind lidar experiment data, and compared the retrieved results with the radiosonde wind profile. The consistency is very good, especially at an altitude above 1.8 km. We may speculate that when the atmosphere flows are not so dramatic, the lidar and the radiosonde measurements are strictly synchronous, it is possible to retrieve horizontal wind speeds and directions consistently with the radiosonde using our wind lidar model and the L-M algorithm. (c) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： airborne wind lidar Doppler optimization algorithm Levenberg-Marquardt algorithm

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Study on the Prediction of Troposcatter Transmission Loss

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2016年第3期64卷 1071-1079页

作者： Li, Lei Wu, Zhen-Sen Lin, Le-Ke Zhang, Rui Zhao, Zhen-Wei Xidian Univ Sch Phys & Optoelect Engn Xian 710071 Peoples R China CRIRP Natl Key Lab Electromagnet Environm Qingdao Peoples R China

In this article, a novel semiempirical average annual troposcatter transmission loss prediction model is presented. The model is generated by optimizing the correlation coefficients of propagation path conditions utilizing the modern optimization algorithm. The statistical relativities of troposcatter transmission loss as captured by changing frequency, path length, scatter angle, and meteorological condition are each analyzed using the terrestrial trans-horizon propagation loss data banks released by the International Telecommunication Union (ITU). For the percentages of time transmission loss not falling below 50%, the model is combined with the model of anomalous propagation mechanism introduced in the Recommendation ITU-R P.2001. The prediction results of this new troposcatter model are compared with other troposcatter models and with the trans-horizon propagation loss data banks. The comparisons show that the new model has a better estimated accuracy.

关键词： Average year optimization algorithm prediction model trans-horizon propagation transmission loss troposcatter

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Modulation of Directionality of Infrared Signatures Based on Anisotropic Emission Behavior

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JOURNAL OF THERMOPHYSICS AND HEAT TRANSFER 2016年第4期30卷 804-813页

作者： Huang, Yong Cui, Xue Beihang Univ Fundamental Sci Ergon & Environm Control Lab Sch Aeronaut Sci & Engn Beijing Univ Aeronaut & Astronaut Mailbox 50537 Xueyuan Rd Beijing 100191 Peoples R China Beihang Univ Fundamental Sci Ergon & Environm Control Lab Sch Aeronaut Sci & Engn Beijing 100191 Peoples R China

A technique for modulating the directional characteristics of the target's infrared signatures based on the anisotropic emission behavior of the target surface is proposed. The integrated infrared transmission model from target to detector is established by matrices. Through the single-, multi-, and omni-directional infrared signature optimization analyses, the effectiveness of the proposed modulation technique is demonstrated and the following conclusions were reached: 1) Because the hemispherical emissivity remains constant, modulating the angular emission patterns of the target surface can enhance or reduce the target's infrared signature level received by the detector. 2) It is possible to adjust the directionality of infrared signatures by virtue of anisotropic emission behavior, generating appreciable peak signals in the desired directions or reducing the infrared signals in the infrared -threatening directions. 3) The optimizing effects upon the directionality of infrared signatures are highly dependent on the geometric features of target and hemispherical emissivity: the smaller the hemispherical emissivity is, the better the effects are.

关键词： Radiation Properties Aircraft Configurations optimization algorithm Transmittance Horizontal Stabilizers Emissive Power Aircraft Wings Spline Interpolation Euler Angles Aerodynamic Heating

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Modeling and parameter identification for a nonlinear multi-stage system for dha regulon in batch culture

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APPLIED MATHEMATICAL MODELLING 2016年第1期40卷 468-484页

作者： Yin, Hongchao Yuan, Jinlong Zhang, Xu Xie, Jun Feng, Enmin Xiu, Zhilong Dalian Univ Technol Sch Energy & Power Engn Dalian 116024 Liaoning Peoples R China Dalian Univ Technol Sch Math Sci Dalian 116024 Liaoning Peoples R China PLA Dalian Naval Acad Dalian 116018 Liaoning Peoples R China Dalian Univ Technol Sch Life Sci & Biotechnol Dalian 116012 Liaoning Peoples R China

The bioconversion of glycerol to 1,3-propanediol (1,3-PD) is a complex bioprocess. In this paper, based on biological phenomena of different characteristics at different stages and the genetic regulation of dha regulon, we consider a fourteen-dimensional nonlinear multi-stage dynamic system with unknown time and system parameters for formulating the multi-stage cell growth in batch culture. Some important properties of the multi-stage system are discussed. Our goal is to identify the time and system parameters. To this end, we present a parameter identification problem in which the time and system parameters are decision variables and the cost function measures the discrepancy between experimental data and computational results, subject to the multi-stage system, parameter constraints and continuous state inequality constraints. The system sensitivity (the cost function's gradient, namely, the derivative of the cost function with respect to the time and system parameters), which can be computed by solving an auxiliary initial value problem, can be regarded as the search direction of optimization algorithm. The identification problem is converted into a sequence of nonlinear programming subproblems through the application of the time-scaling transformation, the constraint transcription and local smoothing approximate techniques. Due to the highly complex nature of the identification problem, the computational cost is high. Thus, a parallel algorithm is proposed to solve these subproblems based on the novel combinations of system sensitivity and genetic algorithm. Finally, numerical results show that the multi-stage system can reasonably describe the process of batch culture. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Nonlinear multi-stage system optimization algorithm Batch fermentation System sensitivity

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Margin-based two-stage supervised hashing for image retrieval

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NEUROCOMPUTING 2016年 214卷 894-901页

作者： Liu, Ye Pan, Yan Lai, Hanjiang Liu, Cong Yin, Jian Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou Guangdong Peoples R China Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou Guangdong Peoples R China Sun Yat Sen Univ Sch Software Guangzhou Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Foshan Peoples R China Sun Yat Sen Univ Sch Adv Comp Guangzhou Guangdong Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore Singapore

Similarity-preserving hashing is a widely used method for nearest neighbor search in large-scale image retrieval. Recently, supervised hashing methods are appealing in that they learn compact hash codes with fewer bits by incorporating supervised information. In this paper, we propose a new two-stage supervised hashing methods which decomposes the hash learning process into a stage of learning approximate hash codes followed by a stage of learning hash functions. In the first stage, we propose a margin-based objective to find approximate hash codes such that a pair of hash codes associating to a pair of similar (dissimilar) images has sufficiently small (large) Hamming distance. This objective results in a challenging optimization problem. We develop a coordinate descent algorithm to efficiently solve this optimization problem. In the second stage, we use convolutional neural networks to learn hash functions. We conduct extensive evaluations on several benchmark datasets with different kinds of images. The results show that the proposed margin-based hashing method has substantial improvement upon the state-of-the-art supervised or unsupervised hashing methods. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Deep learning Image retrieval Image hashing Neural network optimization algorithm

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A novel bidirectional mechanism based on time series model for wind power forecasting

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APPLIED ENERGY 2016年第Sep.1期177卷 793-803页

作者： Zhao, Yongning Ye, Lin Li, Zhi Song, Xuri Lang, Yansheng Su, Jian China Agr Univ Dept Elect Power Syst POB 210 Beijing 100083 Peoples R China CEPRI Beijing 100192 Peoples R China

A novel bidirectional mechanism and a backward forecasting model based on extreme learning machine (ELM) are proposed to address the issue of ultra-short term wind power time series forecasting. The backward forecasting model consists of a backward ELM network and an optimization algorithm. The reverse time series is generated to train backward ELM, assuming that the value to be forecasted is already known whereas one of the previous measurements is treated as unknown. In the framework of bidirectional mechanism, the forward forecast of a standard ELM network is incorporated as the initial value of optimization algorithm, by which error between the backward ELM output and the previous measurement is minimized for backward forecasting. Then the difference between forward and backward forecasting results is used as a criterion to develop the methods to correct forward forecast. If the difference exceeds a predefined threshold, the final forecast equals to the average of forward forecast and latest measurement. Otherwise the forward forecast keeps as the final forecast. The proposed models are applied to forecast wind farm production in six time horizons: 1-6 h. A comprehensive error analysis is carried out to compare the performance with other approaches. Results show that forecast improvement is observed based on the proposed bidirectional model. Some further considerations on improving wind power short term forecasting accuracy by use of bidirectional mechanistn are discussed as well. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Wind power forecasting Wind farm Extreme learning machine optimization algorithm

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Decentralized Cooperative Control Methods for the Modified Weapon-Target Assignment Problem

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2016年第9期39卷 1934-1948页

作者： Volle, Kyle Rogers, Jonathan Brink, Kevin Georgia Inst Technol Sch Mech Engn Atlanta GA 30332 USA US Air Force Res Lab Munit Directorate Eglin AFB FL 32542 USA

Weapon-target assignment is a combinatorial optimization problem in which a set of weapons must selectively engage a set of targets. In its decentralized form, it is also an important problem in autonomous multi-agent robotics. In this work, decentralized methods are explored for a modified weapon-target assignment problem in which weapons seek to achieve a prespecified probability of kill on each target. Three novel cost functions are proposed that, in cases with low agent-to-target ratios, induce behaviors that may be preferable to the behaviors induced by classical cost functions. The performance of these proposed cost functions is explored in simulation of both homogeneous and heterogeneous engagement scenarios using airborne autonomous weapons. Simulation results demonstrate that the proposed cost functions achieve desired behaviors in cases with low agent-to-target ratios where efficient use of weapons is particularly important.

关键词： Airborne Autonomous Weapons Robotics Annealing algorithm Performance optimization algorithm Stochastic optimization Mechanism Design Cost Reduction Search algorithm Unmanned Aerial Vehicle

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Manifold Ranking-Based Matrix Factorization for Saliency Detection

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2016年第6期27卷 1122-1134页

作者： Tao, Dapeng Cheng, Jun Song, Mingli Lin, Xu Yunnan Univ Sch Informat Sci & Engn Kunming 650091 Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Lab Human Machine Control Shenzhen 518055 Peoples R China Chinese Univ Hong Kong Hong Kong Hong Kong Peoples R China Zhejiang Univ Coll Comp Sci Hangzhou 310027 Zhejiang Peoples R China China Three Gorges Univ Hubei Key Lab Intelligent Vis Based Monitoring Hy Yichang 443002 Peoples R China

Saliency detection is used to identify the most important and informative area in a scene, and it is widely used in various vision tasks, including image quality assessment, image matching, and object recognition. Manifold ranking (MR) has been used to great effect for the saliency detection, since it not only incorporates the local spatial information but also utilizes the labeling information from background queries. However, MR completely ignores the feature information extracted from each superpixel. In this paper, we propose an MR-based matrix factorization (MRMF) method to overcome this limitation. MRMF models the ranking problem in the matrix factorization framework and embeds query sample labels in the coefficients. By incorporating spatial information and embedding labels, MRMF enforces similar saliency values on neighboring superpixels and ranks superpixels according to the learned coefficients. We prove that the MRMF has good generalizability, and develops an efficient optimization algorithm based on the Nesterov method. Experiments using popular benchmark data sets illustrate the promise of MRMF compared with the other state-of-the-art saliency detection methods.

关键词： Manifold ranking (MR) matrix factorization optimization algorithm saliency detection

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Shaping Radar Ambiguity Function by L-Phase Unimodular Sequence

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IEEE SENSORS JOURNAL 2016年第14期16卷 5648-5659页

作者： Zhang, Jindong Shi, Changli Qiu, Xiaoyan Wu, Yue Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 210016 Jiangsu Peoples R China Nanjing Univ Aeronaut & Astronaut Nanjing 210016 Jiangsu Peoples R China

In this paper, we discuss the ambiguity function (AF) synthesis problem for unimodular sequences, which are widely used in radar/sonar and communication systems. Notions of discrete-time ambiguity function and discrete ambiguity function (DAF) are defined, and the corresponding properties are also discussed for unimodular sequences. Depending on these properties, two algorithms are proposed to synthesize the DAF of the unimodular sequence by minimizing the squared error between a desired complex/real function and a realizable one over L-phase alphabet. To break the volume invariant constraint of a single sequence's AF, multi-sequences are also considered to be optimized simultaneously to suppress sidelobes of ambiguity surface. Numerical examples show the effectiveness of the proposed algorithms in synthesizing unimodular sequence with a desired AF, and typical polyphase sequences can be well approximated by eight-phase unimodular sequences from the viewpoint of DAF.

关键词： Ambiguity function shaping unimodular sequence optimization algorithm discrete-time ambiguity function discrete ambiguity function

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High-speed optical FSK demodulator using plasmonic nano bi-dome

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OPTIK 2016年第19期127卷 8030-8035页

作者： Akhlaghi, Majid Islamic Azad Univ Omidiyeh Branch Young Researchers & Elite Club Omidiyeh Iran

An optical frequency-shift-keying demodulator with ultra-small plasmonic nano bi-domes that can filter the coherent optical frequency is developed. Since filtering efficiency depends strongly on the position and number of the plasmonic nano bi-domes in the array, binary Teaching-Learning-Based optimization (BTLBO) algorithm is proposed to design an array of plasmonic nano bi-domes in order to achieve maximum absorption coefficient spectrum. In BTLBO, a group of learner consists a matrix with binary entries;control the presence ('1') or the absence ('0') of nano particles in the array. (C) 2016 Elsevier GmbH. All rights reserved.

关键词： Optical devices Plasmonic nano particles optimization algorithm

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