bluuebunny/crossref_metadata_2025 huggingface dataset:
CVABS: moving object segmentation with common vector approach for videos
Authors: Işık Şahin , Özkan Kemal , Nezih Gerek Ömer
Published: October 2019

Background modelling is a fundamental step for several real‐time computer vision applications that requires security systems and monitoring. An accurate background model helps to detect the activity of moving objects in the video. In this work, the authors have developed a new subspace‐based background‐modelling algorithm using the concept of common vector approach (CVA) with Gram–Schmidt orthogonalisation. Once the background model that involves the common characteristic of different views corresponding to the same scene is acquired, a smart foreground detection and background updating procedure is applied based on dynamic control parameters. A variety of experiments is conducted on different problem types related to dynamic backgrounds. Several types of metrics are utilised as objective measures and the obtained visual results are judged subjectively. It was observed that the proposed method stands successfully for all problem types reported on CDNet2014 dataset by updating the background frames with a self‐learning feedback mechanism.
Position sensorless control for doubly salient electro‐magnetic motor based on the terminal voltage
Authors: Liu Weifeng , Wang Huizhen , Wang Yongjie , Xiao Lan , Huang Zelei
Published: October 2019

A sensorless control method based on the terminal voltage for doubly salient electro‐magnetic motor (DSEM) is researched here. The negative‐going zero‐crossing point (NGZCP) of the fundamental component of terminal voltage is detected to obtain the rotor position. Firstly, a fourth Butterworth filter is introduced to extract the fundamental component of the terminal voltage. The ratio of signal frequency to cut‐off frequency f/fc is optimised to acquire good filtering effect and good dynamic performance. Moreover, on this basis, the speed range is divided into several intervals to match the filters with different cut‐off frequencies. Secondly, the coordinate transformation is adopted to compensate for the phase difference between the NGZCPs of the extracted voltages with the ideal commutation points. The transformation angle is obtained by offline simulation and test. An 18 kW DSEM prototype is tested to verify the feasibility of the proposed method.
Online maximum torque per ampere control for induction motor drives considering iron loss using input–output feedback linearisation
Authors: Mosaddegh Hesar Hamidreza , Abootorabi Zarchi Hossein , Ayaz Khoshhava Mojtaba
Published: October 2019

This study presents a novel online, accurate and simple model‐based maximum torque per ampere (MTPA) strategy for input–output feedback linearisation control of induction motor (IM) drives. Despite conventional MTPA control principles which are under the assumption of iron loss neglecting, the proposed strategy takes iron loss effect into account. This study highlights the iron loss influence on MTPA scheme. Firstly, the cross‐coupling effects in the IM model and torque non‐linearity due to the iron loss in torque–speed characteristics of the IM are discussed. The criterion for the MTPA scheme is then introduced and investigated by gradient approach so that when the gradient vectors of the torque and stator current magnitude are parallel, the MTPA strategy is satisfied. Finally, to confirm the validity of the proposed control scheme, experiments are carried out.
Electromagnetic force density calculation in surface‐mounted PM synchronous machine with rotor eccentricity by an equivalent transformation method
Authors: Ren Jie , Wang Xiuhe , Zhao Wenliang , Peng Bo
Published: October 2019

An equivalent transformation method is proposed to calculate the electromagnetic force density of surface‐mounted permanent magnet (PM) synchronous machine with static and dynamic eccentricities. It hypothetically transforms the original, eccentric machine into a concentric one with redistributed PM remanence and current density according to equivalent transformation principle. On the basis of the magnetic field of the concentric machine obtained by the subdomain method, the air‐gap flux density of the eccentric machine is then achieved. Finally, the electromagnetic force density is predicted by the air‐gap field based on Maxwell stress tensor method and analysed by the two‐dimensional Fourier transform. The effectiveness of this method is verified on both static and dynamic eccentricities conditions by the finite‐element method and experiment.
Radial position control for magnetically suspended high‐speed flywheel energy storage system with inverse system method and extended 2‐DOF PID controller
Authors: Chen Liangliang , Zhu Changsheng , Zhong Zhixian , Wang Changkun , Li Zhinong
Published: October 2019

To achieve high‐precision position control for the active magnetic bearing high‐speed flywheel rotor system (AMB‐HFRS), a novel control strategy based on inverse system method and extended two‐degree‐of‐freedom (2‐DOF) proportional–integral–derivative (PID) controller is proposed in this study. First, the inverse system method is employed to decouple the AMB flywheel rotor system with strong non‐linear and coupling, into four independent subsystems. Subsequently, extended 2‐DOF PID controllers are used to regulate the decoupled subsystems, to obtain good performances of disturbance rejection and tracking simultaneously. In the extended 2‐DOF PID controller, a differential signal is produced by a velocity observer to improve the ability of against noise. Finally, the characteristics of stability, tracking, disturbance rejection and robustness of the control strategy proposed are analysed in theory, and its ability and effectiveness to control the radial position of the AMB‐HFRS are further studied by simulations and experiments. It is shown that the control strategy proposed can keep the AMB‐HFRS suspending stably from static state to the speed of 24,000 rpm, has the advantages of good tracking, high disturbance rejection, strong robustness and good ability of against noise.
New approach to transient stability prediction of power systems in wide area measurement systems based on multiple‐criteria decision making theory
Authors: Hosseini Hossein , Naderi Soheil , Afsharnia Saeed
Published: October 2019

To prevent power system blackouts following a large disturbance such as a fault, the speed and precision of the stability status prediction are two important factors for the remedial action schemes. A new approach for the transient stability prediction is presented employing the multi‐criteria decision making (MCD) theory to consider both factors simultaneously in this study. It is shown that they depend on the prediction time, therefore solving the MCD problem results in finding the best time for the stability prediction. As the criteria quantifying is necessary in the MCD methods, in this study a new index is proposed to quantify the prediction speed. Furthermore, the support vector machine (SVM) classifier is employed as a transient stability predictor. In addition, the best features are selected and incorporated as the inputs of the SVM classifier according to the features selection methods. Finally, all proposed schemes are implemented on the IEEE 39‐Bus test system. The obtained results show the prediction of stability at the optimum time causing the instability prevention with the less required remedial action.
Two‐stage stochastic operation framework for optimal management of the water–energy–hub
Authors: Kavousi‐Fard Abdollah , Su Wencong , Jin Tao , Papari Behnaz
Published: October 2019

This study proposes a bi‐level stochastic framework to address optimal scheduling of energy hub (EH) in a pool‐based short‐term market considering electrical–thermal–water demands. EH acts as an independent price‐maker producer in a day‐ahead electricity market aiming to maximise its profit. The market settlement mechanism is constructed as the pay‐at‐market‐clearing price (MCP), where each producer/consumer is paid at the MCP. The problem model is formulated as a bi‐level optimisation approach in a stochastic environment, in which the upper level defines the profit maximisation of the proposed strategic producer, whereas the lower‐level expresses the dispatch cost of the considered power grid. This results in a problem formulation with mathematical equilibrium constraints which is transformed into a new mixed‐integer linear programme based on Karush–Kuhn–Tucker conditions. A stochastic framework based on unscented transform is developed to model the high uncertainties of EH water demand, EH thermal demand, EH electric demand, generators and loads submitted price to the market. The simulation results on the IEEE test system advocate the effectiveness and appropriate performance of the proposed strategic EH producer in the electricity market and its effect on the locational marginal prices of buses in a transmission‐constrained market.
Supervised fusion approach of local features extracted from SAR images for detecting deforestation changes
Authors: Horch Abdelkader , Djemal Khalifa , Gafour Abdelkader , Taleb Nasreddine
Published: October 2019

Deforestation has become a major problem consisting of a continuous regression of forested areas in the world, and for this purpose, an efficient detection of these changes has become more than necessary. In this work, a new method for deforestation change detection is proposed. This approach is based on a supervised fusion of local texture features extracted from SAR images. ALOS PALSAR (Advanced Land Observation Satellite Phased Array type L‐band Synthetic Aperture Radar) multi‐temporal data have been used in this work. Normalised radar cross‐section (NRCS) and polarimetric features extracted from HH and HV polarised data allowed recognising different categories of land covers termed as NRCS classification. Grey‐level co‐occurrence matrix (GLCM) texture features were extracted by using a different moving window sizes applied on local regions previously obtained by binarisation of the NRCS results. A total of 300 samples of regions and five GLCM characteristics have been used here. The detection of deforestation appears clearly in the resulted images with a very satisfactory precision of the reached regions, and the obtained results of the proposed supervised approach have indeed led to very good detection results of the deforestation change.
Big spatio‐temporal data mining for emergency management information systems
Authors: Dagaeva Maria , Garaeva Alina , Anikin Igor , Makhmutova Alisa , Minnikhanov Rifkat
Published: October 2019

Nowadays, spatio‐temporal data analytics plays an important role in different applications based on geographic information system (GIS). One of such applications is emergency management information systems (EMISs) which process a huge amount of spatio‐temporal data that can be considered as Big Data (BD). Effective EMIS data analysis will allow authorities to improve the management of emergency events, including those related to traffic problems (traffic accidents, traffic jams, etc.). However, the stack of modern technologies dealing with BD does not provide natively supported functions for spatio‐temporal data analysis, so they have to be developed and implemented for EMIS. In this study, the authors developed and evaluated several algorithms and a framework for big spatio‐temporal data mining in the Russian EMIS GLONASS + 112112. They suggested improved spatio‐temporal co‐location patterns mining technique based on DBSCAN, FPGrowth, and natural language processing (NLP). They detected spatio‐temporal outliers and spatial autocorrelation. Finally, they evaluated the scalability and time performance of algorithms. They found that using NLP and aggregation of an emergency dataset with weather to enhance the number of emergency categories could significantly increase the quality of association rules. They discovered valuable association rules related to traffic accidents in the dedicated area of Kazan city.
Miniaturised MIMO antenna array of two vertical monopoles embedded inside a planar decoupling network for the 2.4 GHz ISM band
Authors: Isaac Ayman A. , Al‐Rizzo Hussain , Yahya Samer , Al‐Wahhamy Abbas , Tariq Sulaiman Z.
Published: October 2019

This study introduces a fundamentally new approach to suppress mutual coupling among two closely‐spaced vertical monopole elements of a multiple‐input multiple‐output antenna array. The 40 × 40 × 1.27 mm decoupling and matching element consists of a single planar ring resonator acting as a stop‐band filter along with two tuning strips printed on an ungrounded substrate surrounding a two‐element co‐planar waveguide‐fed monopoles separated by 8 mm (λ0/16) at 2.45 GHz. Measurements reveal 14.2% bandwidth centred at 2.395 GHz over which the decoupling is below 20 dB, and −10‐dB impedance bandwidth of 19.5% centred at 2.36 GHz. An improvement of 43 dB in isolation is observed at a frequency of 2.38 GHz. It is shown that the decoupled array provides a total realised gain of 1.69 dBi with excellent diversity performance as demonstrated by the low envelope correlation coefficient and improved link efficiency in highly‐correlated channel environments due to the spatially orthogonal 3D radiation patterns. The capacity offered by the decoupled array is enhanced by 50, 22, 18 and 12% at signal‐to‐noise ratios of 5, 20, 30, and 50 dB, respectively, as compared to the coupled array in an urban micro‐channel spatial model.
Modelling approach for multi‐carrier‐based pulse‐width modulation techniques utilised in asymmetrical cascaded H‐bridge inverters
Authors: Soltani Mohammad , Pairo Hamidreza , Shoulaie Abbas
Published: October 2019

The increasing use of medium‐voltage drives and high‐power equipment requires a detailed study on the switching method and topology of multi‐level inverters. Asymmetric cascaded H‐bridge topologies that have unequal input dc voltages with different devices in various parts of the cascaded H‐bridge inverter (CHB) are representative of significant improvements in medium‐voltage industrial drives. Various modulation strategies are used in multi‐level power conversion applications. In the multi‐carrier switching method for asymmetric CHB, the number of switches is less than carriers and is usually used in the off‐line switching method. These methods of switching are not applicable to online systems. In this study, equations for combining different pulse‐width modulation (PWM) to use the controllability advantage of the multi‐carrier method are introduced in asymmetric topologies. Then, the dual Fourier series equations are applied to model each inverter switching relation of the asymmetric cascaded blocks. To model each inverter switching relation of the asymmetric blocks using sinusoidal PWM, the dual Fourier series equations were applied. The presented analytical modelling switching method was validated using simulation and experimental case studies.
Modulation‐controlled clamped‐three‐level inverters supplied by series unbalance battery‐banks under asymmetric SOCs
Authors: Hashempour Mohammad M. , Liu Fang‐Ta , Lee Tzung‐Lin
Published: October 2019

Energy storage systems can be utilised to counteract unreliability of renewable energy sources. This study proposes a novel modulation for clamped‐three‐level inverters when the dc link of inverter contains two series‐connected battery banks. By proposed modulator matched with the considered topology, inverter is free from over‐modulation even under unbalance neutral‐point voltage. In addition, by appropriate zero‐sequence common mode voltage injection, neutral‐point current is controlled and batteries’ state of charge (SOC) are dealt with so that power generation in discharge mode or power absorption in charge mode is properly shared between batteries. Due to the high capability of the proposed method, output voltage and current of inverter are almost free of low‐order harmonic distortion even under severe unbalance condition and/or great asymmetric SOCs. After analysing and rejecting previous modulation‐based control strategies for the considered topology, simulation study (charge and discharge modes) and experimental validations (discharge mode) are provided to verify the proposed method in grid‐connected and islanded systems under different power factors.
Two stages K‐means and PSO‐based method for optimal allocation of multiple parallel DRPs application & deployment
Authors: Ibrahim Charles , Mougharbel Imad , Kanaan Hadi Y. , Abou Daher Nivine , Georges Semaan , Saad Maarouf
Published: October 2019

Different types of Demand Response Programmes (DRPs) exist and can be simultaneously offered by the electrical utilities through established contracts with customers. Operating simultaneously multiple types of DRPs might lead to undesired results. DRPs might have different responses to objectives, time‐based ones tend to maximise consumption during lowest tariffs periods while incentive‐based ones tend to reduce the usage based on peak events, accordingly contradiction might occur. Thus, synchronising these DRPs and their parameters through an optimised process including customer selection for the appropriate one is a mandatory step. A fair allocation of the various types of DRPs including their execution's priority at a specific time is the main objective of this study. An original approach based on clustering technique for predicting customers' behaviour coupled with a particle swarm optimisation (PSO) to reach an optimal solution for relocation is presented. In this study, an optimal solution is developed; it provides the various DRPs with the most convenient parameters for the best demand/generation balance, utility profit maximisation and operational cost minimisation. The method is validated through a simulation applying a time‐based with two incentive‐based DRPs in the presence of conventional and renewable generation while using Kmeans clustering and PSO on Matlab.
Cloud connection oriented real‐time monitoring system for atmospheric particles
Authors: Bao Li‐qun
Published: October 2019

To meet the requirements of data acquisition from mobile pollution sources and unfixed data acquisition points in atmospheric particle monitoring system, this study designs a real‐time monitoring system for atmospheric particles such as PM2.5 based on a single‐chip microcomputer, an ET‐iLink open cloud platform and an Android operating system. The movable data acquisition nodes for atmospheric particles are designed. The laser scattering method is used to obtain the data of atmospheric particle concentration, which are uploaded to the cloud platform through the GPRS network. The Android application obtains the real time data of atmospheric particle concentration from the cloud platform. Thus the real‐time remote monitoring for atmospheric particles is realised. The test results show that the system has the following advantages: stable performance, high scalability and low error rate.
Robust adaptive beamforming with low sensitivity for mutual coupling based on auxiliary elements
Authors: Zhang Tao , Zhang Guanglei , Li Xiaoming
Published: October 2019

The performance of the conventional adaptive beamformer undergoes degradation in the presence of the mutual coupling between the neighbouring elements. To eliminate the sensitivity for the MC, the dummy elements are fixed around the array. Here, the authors demonstrate the optimal layers of auxiliary elements for uniform rectangular array (URA) in the case of the specific MC model and give the concrete theoretical proof. The corresponding derivation proves that only one layer of auxiliary elements is needed to tackle with the MC effect, and the output SINR and beampattern are improved by means of the proposed method for URA. Finally, the simulation results have shown the effectiveness of authors’ method.
Sparse Bayesian learning‐based mainlobe blanket jamming suppression algorithm
Authors: Zhou Bilei , Duan Keqing , Liu Weijian , Li Rongfeng , Wang Yongliang
Published: October 2019

The suppression of mainlobe jamming (MLJ) is a hard task and an open problem in the electronic counter‐countermeasures field. In this article, a sparse Bayesian learning (SBL)‐based mainlobe blanket jamming suppression algorithm is proposed for solving this problem, which can effectively suppress the MLJ and estimate the target distance and direction. The proposed algorithm can be divided into two steps. First, the row (or column) spatial adaptive processing is adopted to suppress the MLJ; Second, the SBL algorithm is used to obtain the target echo parameters.
Robust boundary extraction of great lakes by blocking Active Contour Model using Chinese GF‐3 SAR data: a case study of Danjiangkou reservoir, China
Authors: Niu Shilin , Li Ning , Guo Zhengwei , Wang Robert , Guo Yuexiu , Wu Lin , Zhao Jianhui
Published: October 2019

Chinese Gaofen‐3 (GF‐3) satellite is a spaceborne multi‐polarisation synthetic aperture radar (SAR) mission in C‐band and it can be applied in the multiple fields. GF‐3 can achieve accurate water boundary extraction based on its high‐resolution SAR image products. This paper will study GF‐3's capability to extract water boundary. Danjiangkou reservoir, the largest artificial freshwater lake in Asia and water source of Chinese South‐to‐North Water Diversion Project, is selected as the study region. A novel segmentation method is proposed which consists of two parts: the first part is rough segmentation to get the initial boundary; the second part is fine segmentation to get the final water boundary. Experimental results show that GF‐3 has good performance in water boundary exaction by virtue of this novel method.
Clutter modelling and simulation for hypersonic vehicle‐borne radar
Authors: Zhang Mengdi , Liao Guisheng , Zhu Shengqi
Published: October 2019

Hypersonic vehicles (HSV) have attracted much attention in recent years because of its military value. The radar system will face more serious clutter problem due to the increasing altitude and velocity. Thus, clutter characteristics analysis of hypersonic vehicles radar (HSV‐R) is essential to clutter suppression. In this study, clutter model for HSV‐R is proposed and the selection of pulse repetition frequency (PRF) is discussed. Finally, the results of simulation and the analysis of clutter characteristics under different PRFs are given.
High‐sensitive acquisition method of GPS signal based on iridium assistance
Authors: Zihuan Hao , Lei Zhang
Published: October 2019

Global positioning system (GPS) signal is severely attenuated in indoor, urban, and forest environments. To capture weak GPS signal, long‐time coherent integration and non‐coherent integration are used to increase signal to noise ratio (SNR). However, coherent integration time is constrained by Doppler frequency and navigation message, and the non‐coherent integration has square loss. Assisted GPS (AGPS) can effectively prolong the coherent integration time, but it is costly and has poor performance in rural areas. An Iridium‐assisted acquisition method is proposed here. The coherent integration time can be prolonged with Iridium‐assisted values of code phase, Doppler frequency, and navigation message. This method can effectively improve the acquisition sensitivity and reduce the average acquisition time. The Monte–Carlo simulation results show that the capture sensitivity can reach 15 dB‐Hz (CNR) with 200 ms coherent integration.
ωk algorithm for multi‐receiver synthetic aperture sonar based on exact analytical two‐dimensional spectrum
Authors: Wang Jinbo , Tang Jinsong , Tian Zhen
Published: October 2019

Based on the method of deriving two‐dimensional wavenumber spectrum by using instantaneous Doppler wavenumber in bistatic synthetic aperture radar, the analytical solution of two‐dimensional wavenumber spectrum of multi‐receiver synthetic aperture sonar (SAS) was deduced, and the analytical expression of the half‐quasi‐bistatic angle was obtained under the non‐stop‐and‐go assumption. Based on the derived two‐dimensional wavenumber spectrum, the ωk algorithm suitable for multi‐sub‐array SAS was proposed, which solved the problem that using the displacement phase centre approximation cannot well adapt to the wide mapping area imaging, and the correctness and validity of the algorithm have been verified by the simulation data and the lake experiment data.
Analysis of polarisation features of typical targets in Chengdu using GF‐3 fully polarimetric synthetic aperture radar data
Authors: Wang Xiaoxia , Zhang Wei , Ding Qing , Zheng Changli , Luo Jinghui
Published: October 2019

The fully polarimetric synthetic aperture radar (SAR) data contain much backscatter intensity information and have great advantage for land monitoring. Analysing the polarisation features of typical targets is a critical step for landing monitoring, especially the ground objects identification, and thus accurately obtaining and analysing the polarisation features is of importance. Gaofen‐3(GF‐3) is the first C band fully polarimetric SAR satellite in China, which is widely used in various fields such as land monitoring, disaster reduction and so on. Here, the GF‐3 fully polarimetric SAR data at three time‐slices were used to obtain and analyse the polarisation features of typical targets in Chengdu. The results revealed the scattering type of the typical targets including artificial buildings and vegetation and indicated that the GF‐3 SAR data were suitable to be used for obtaining polarisation features of typical targets and have the potential for discriminate artificial building and further for landing monitoring.
Research on modern radar emitter modelling technique under complex electromagnetic environment
Authors: Zhang Chunhong , Han Yuetao , Zhang Ping , Song Guanglei , Zhou Changqing
Published: October 2019

Since many modern multi‐functional radars emitting dense complex signals are applied in the complex electromagnetic environment, it is challenge to classify and identify the radar emitters in the electronic reconnaissance field. In order to classify and identify radar emitters accurately and rapidly, a kind of standard adaptive extended radar emitter modelling structure and the complete process of obtaining radar emitter model parameters are proposed in this study. The simulation analysis results show that the proposed standard modelling structure and complete process can rapidly realise the accurate classification of many multi‐functional radar emitters; hence can further benefit to accurate identification of emitters.
Improved scheme for clutter rejection and DOA estimation in passive radar
Authors: Wang Ke , Wan Xianrong , Yi Jianxin , Yi Yucheng
Published: October 2019

Targets are hard to be detected by passive radars unless clutter, namely direct‐path signal and multi‐path signal, is suppressed. The subcarrier‐based spatial adaptive processing is a high‐performance spatial‐domain clutter rejection algorithm. It may have adverse influence on the direction of arrival (DOA) estimation. The study analyses the influence theoretically and proposes an improved processing scheme to avoid the influence. Experimental results using real data validate the proposed scheme.
Weather surveillance radar as an objective tool for monitoring bat phenology and biogeography
Authors: Stepanian Phillip M. , Wainwright Charlotte E. , Frick Winifred F. , Kelly Jeffrey F.
Published: October 2019

Bats provide a wealth of vital services to humans, such as pollinating plants and managing populations of insects that act as agricultural pests and disease vectors. Despite their direct importance, it is inherently difficult to monitor bats across large spatiotemporal scales, in part due to their nocturnal activity and long‐distance, high‐altitude flights. Networks of weather surveillance radars provide continuous measurements of the airspace at continental scales, revealing the abundance, distribution, behaviour, and phenology of bats aloft. Using a network of polarimetric Doppler weather radars in the USA, we demonstrate applications of this technology to monitor large bat colonies, highlight recent discoveries made using radar surveillance of bats, and discuss future prospects for extending these techniques as part of a standardised system of global bat monitoring infrastructure.
Direct wave suppression technology of passive radar system
Authors: Xiaohang Ren , Ning Liu , Jinghua Wang , Running Zhang
Published: October 2019

This work studies the direct wave suppression technology of passive radar system based on ‘global system for mobile (GSM)’ communication. In order to suppress direct waves, this study proposes an adaptive suppression algorithm based on NLMScriterion. Achieves great suppression of the strong interference signal, and finally realised target positioning and velocity measurement to the actual measured GSM signal.
Waveform design for cognitive radar in presence of jammer using Stackelberg game
Authors: Li Kang , Jiu Bo , Liu Hongwei , Liang Siyuan
Published: October 2019

With the development of modern electronic warfare, the jammer is becoming smarter than before and can be able to take actions according to the intercepted radar waveform. It has considerable significance for the radar to design a proper waveform to improve its performance when facing the smart jammer. Here, a novel cognitive radar waveform design method is proposed to improve the radar's performance. The relationship between the radar and the jammer is modelled as a two‐person zero‐sum Stackelberg game, where the cognitive radar is the leader and the jammer is the follower. Signal‐to‐interference and noise ratio (SINR) criterion is utilised as the utility function, where the radar tries to maximise the SINR while the jammer aims to minimise it. Lagrange multiplier method and particle swarm optimisation (PSO) algorithm is applied to solve the problem and the Stackelberg equilibrium (SE) is obtained. Numerical results show the effectiveness of the proposed method.
Data compression method based on information preservation for wideband radar LFM signal echo
Authors: Gao Lei , Zeng Yong‐hu , Wang Lian‐dong , Wang Wei
Published: October 2019

With the increase of radar signal bandwidth and the application of RF directing sampling technology, wideband radars are facing greater pressures for data transmission, storage, and processing. Based on the relationship between linear frequency modulation (LFM for short) signal and LFM‐stepped signal, synthesis method of high‐resolution range profile (HRRP for short) for LFM step signal can be applied to LFM signal. Combining the synthesis method of HRRP for LFM signal with compressed sensing theory, this study proposes a new compression method for wideband radar echo with LFM signal style based on random segment selection and analyses the constraint conditions of the proposed data compression method. Finally, the validity and practicability of the proposed data compression method are verified from two aspects: simulation experiment and actual data processing.
Adaptive signal suppression based on modified PCA for a single‐point radiation source in radar networks
Authors: Miao Yingjie , Liu Feifeng , Tian Lun , Liu Quanhua
Published: October 2019

In order to realise effective target detection with a large baseline radar network interfered by a single radiation source, an adaptive processing method derived from traditional principal component analysis (PCA) and array signal processing theory is proposed in this study. First, the signal model for target detection with a large baseline radar system in an interference environment is established. Second, based on the characteristics of the signal model, an adaptive suppression method composed of high‐precision delay alignment and modified PCA is proposed. Finally, the effectiveness of the method in a typical environment is verified by simulation. The results show that this method can accumulate target energy effectively and realise reliable detection in such case, which has great application prospects.
Applicable STAP for moving FOD detection
Authors: Yang Xiaoqi , Huo Kai , Zhang Xinyu , Jiang Weidong
Published: October 2019

Serious security risks and economic losses have increased rapidly under the threat of foreign object debris. Most detection methods employing optical devices are limited in severe weather for low visibility. This study proposes an applicable approach for moving foreign object debris on the basis of space‐time adaptive processing. The geometrical model of an airport is introduced whereby the runway and lawn are divided into clutter cells. After calculating the complex amplitude of clutter in each cell, the authors employ the minimum variance power spectrum and degrees of freedom to describe the ground clutter characteristics. Then the space‐time filter is designed under the linearly constrained minimum variance criterion to suppress the clutter and detects the moving target. Simulations show that the errors in azimuth and Doppler are both less than −15 dB when SCNR = −20 dB.
Bi‐level JOMP for DOA estimation in coprime array with off‐grid targets
Authors: Jiang Ying , He Minghao , Tang Yuwen , Han Jun , Fan Xikun
Published: October 2019

The direction of arrival (DOA) estimation for off‐grid targets in the coprime array, which can extend degrees of freedom, is studied. Among existing research results, joint orthogonal matching pursuit (JOMP) has obvious advantages in complexity, but drawbacks in accuracy. Therefore, a bi‐level iterative algorithm is proposed to improve estimation performance of JOMP in this study. First, JOMP is executed to obtain the initial estimations of DOAs and mismatch parameters. Then, an iterative proximity searching is implemented to update target vectors to decline the residual further. After that, on the strength of results of the secondary iteration, the signal spectrum and mismatch parameters can be obtained through exploiting LS algorithm. Simulation results verify effectiveness of the proposed algorithm.
Target tracking with a dynamic and adaptive selection of radars based on entropy
Authors: Li Chunxia , Zhang De , Ge Jianjun , Wang Wujun
Published: October 2019

In the modern rapidly changing battlefield, the resources of multiple radars are usually limited for multiple objects multiple missions. Moreover, the amount of target information acquired by different radars at different time index is different. Thus, as to target tracking, it is important to reasonably and dynamically allocate radars’ resources. In the study, based on information theory, the entropy is utilised to quantitatively measure the amount of target information observed from multiple radars. Corresponding, the lower bound (LB) of the given entropy is also derived. The smaller the value of the entropy, the more accurate the estimate of target motion state is. So based on minimising the entropy LB of target information acquired from radars at different times, a new fusion tracking method is proposed to dynamically adaptively choose radars with high amount of target information for target tracking. The simulation results show that the proposed method has higher tracking accuracy than the fusion tracking without optimal choice of radars.
Joint estimation of DOA and channel errors with sparse recovery for SKA low‐frequency array
Authors: Zhang Fuqiang , Zhang Zenghui , He Jin , Yu Wenxian , Cao Rui
Published: October 2019

Here, the authors present an improved and fast sparse recovery method for joint estimation of channel errors and direction of arrival (DOA) for square kilometre antennas low‐frequency array. Since this array is formed of a large number of antennas and distributed in a very large space, array calibration is a vital step to provide accurate signal information. Then, channel errors are the concerns here, which are assumed to be localised in a priori known interval. To achieve the joint estimation, an approach is proposed by using the alternative optimisation strategy, which theoretically gives convergence results. In detail, the basis pursuit de‐noising (BPDN) algorithm and the proximal algorithm are used to estimate the DOA and the array errors, respectively, and the final results are obtained by alternatively solving these two algorithms. Finally, numerical simulation results are presented to demonstrate the effectiveness of their proposed method.
Narrow band space scanning two‐dimensional linear frequency diverse array radar
Authors: Çetiner Ramazan , Hizal Altunkan
Published: October 2019

Two–dimensional (2D) linear frequency diverse array (FDA) concept is extended to scan a 2D wide angular sector. This is achieved by highly unequal frequency increments in orthogonal 2D directions of the array. The radar operates as a pulsed FDA in the transmission (TX) mode, while it operates as a pulsed phase array (PA) in the receiving (RX) mode. The low energy of the TX FDA waveform is compensated by the rapid 2D angular scanning together with the use of the cumulative probability of detection scheme.
Fast DBF for conformal arrays based on 2D Fourier decomposition
Authors: Yao Yuan , Wu Guangxin
Published: October 2019

Digital array radars with conformal arrays are attractive for platforms with limited installation space such as aircraft and unmanned aerial vehicles. Low‐complexity digital beamforming (DBF) scheme is of great importance for conformal arrays with arbitrary geometry for real‐time applications. This study presents two kinds of two‐dimensional (2D) Fourier bases for the orthogonal decomposition of arbitrary array manifold. The sampling matrix (2D Fourier spectra) can be obtained from the 2D DFT of the array calibration data, facilitating fast DBF scheme for conformal arrays. Moreover, the second 2D Fourier basis can be used to rotate a function on . The modelling accuracy and complexity of different 2D Fourier representations are compared by numerical results and the rotation of functions on is demonstrated.
Radar HRRP recognition based on CNN
Authors: Song Jia , Wang Yanhua , Chen Wei , Li Yang , Wang Junfu
Published: October 2019

In this study, ground target recognition based on one‐dimensional convolutional neural network (CNN) is studied by exploiting the targets’ high‐resolution range profiles (HRRPs). Contrary to conventional methods which need feature extraction artificially, CNN can automatically discover features for classification. The authors propose a multi‐channel CNN architecture that can be applied on diverse forms of HRRP such as amplitude, complex, spectrum etc. Experimental results demonstrate the superiorities of the proposed method over conventional methods based on handcrafted features and single‐channel CNN in terms of recognition accuracy. Visualisation of the ‘deep features’ shows higher separability than handcrafted features, thus providing an insight into its effectiveness in exploiting the intrinsic structures.
RBM‐based joint dictionary learning for ISAR resolution enhancement
Authors: Ye Jiaqi , Qin Dan , Zhang Yifan , Gao Xunzhang
Published: October 2019

In this study, an inverse synthetic aperture radar (ISAR) image resolution enhancement algorithm based on joint dictionary learning is proposed, by which two special sets of sparse signals called dictionaries are solved by exploiting numerous high‐resolution (HR) and low‐resolution (LR) ISAR images. Herein a new coupled dictionary learning algorithm based on restricted Boltzmann machine (RBM) is designed to learn a LR and a HR dictionary using LR and HR image patches. Since the echoes are equivalent to similar scattering‐centre models when an object is illuminated by radar signals with same centre frequency and different bandwidth, respectively, it is reasonable to assume the object's LR ISAR image shares the same sparse representation coefficients with its HR ISAR image. When a LR ISAR image is represented sparsely with a LR dictionary, a HR ISAR images can be reconstructed based on a HR dictionary owing to the similar sparse representation coefficients. Experiment results with simulation data demonstrate the superior performance of the proposed method over other classical dictionary training algorithms.
Adaptive manoeuvring target tracking algorithm based on acceleration pre‐estimation model
Authors: Jian Shen , Jiwei Tang , Hanxi Zhao , Yusheng Yu
Published: October 2019

For the defect of requiring artificially set manoeuvring parameters in traditional target models, an adaptive manoeuvring frequency tracking algorithm based on acceleration pre‐estimation model (APM) was proposed. On the basis of APM, which has a better target tracking performance compared with current statistic model, this study used residual vector to determine variance of target's manoeuvring, and realised an adaptive adjustment for manoeuvring frequency by using a non‐linear function, solved the problem of requiring artificially set manoeuvring frequency in APM. The simulation results showed that the improved algorithm effectively ameliorated the target tracking performance.
Angular glint compensation for seekers based on multicarrier techniques
Authors: Li Haoxing , Zhu Di , Lv Ruiheng , Chen Chen , Zhang Di , Gu Cunfeng , Chen Feng
Published: October 2019

To solve the problem caused by angular glint in the terminal guidance process, which effects steady target tracking and results in the final miss, the influence of angular glint on the seeker's angle tracking and angular glint compensation methodology using multiple output angle error equation with different detection frequencies at single sensing period to extract the unknown parameters of the target model based on the orthogonal multicarrier technique is proposed here. The method is verified reasonable and feasible through the simulation analysis, the analysis result can be applied to improve the tracking precision of the seeker's terminal guidance process.
Deceptive multiple false targets jamming recognition for linear frequency modulation radars
Authors: Du Congju , Zhao Yuan , Wang Lu , Tang Bin , Xiong Ying
Published: October 2019

This study considers the problem of deceptive multiple false targets jamming recognition. Due to the different modulation patterns, there is a great difference in fast‐time frequency spectrum or slow‐time Doppler spectrum between the different types of jammings. The proposed algorithm first extracts the received sample matrix, then computes left and right similarity (LR‐similarity) by fast‐time‐slicing or slow‐time‐slicing process and finally recognises the samples according to template matching classifier. Experimental results demonstrate that the accuracy recognition probability of the proposed method is >95%, when jamming‐to‐signal ratio is above 3 dB.
Dimension degradation of fractionally spaced super‐exponential algorithm for sparse channel equalisation
Authors: Bai JinLiang , Jiang ZhiYe , Wang Feng , Zhou Yi , Sun Heng
Published: October 2019

Fractionally spaced super‐exponential (FSSE) algorithm has the disadvantage of computational complexity since it exploits high‐order statistics explicitly. The authors propose a dimension degradation technique for FSSE when it is applied to the equalisation of a sparse channel in accordance with the relationship between the coefficients of the cross fourth‐order cumulant (CFOC) in FSSE and the channel impulse response. They implement partial updating on the prominent coefficients of the CFOC with all the small coefficients remaining unchanged. The computational complexity of the modified FSSE reduces significantly with an acceptable performance loss, and its performance is validated via numerical simulations.
Intensity gradient based edge detection for pixelated communication systems
Authors: Kabir Md Ahasan , Mondal Md Rubaiyat Hossain
Published: October 2019

Pixelated optical communication systems transmit data using a series of encoded pixelated images. The decoding of these pixelated images is important for reliable data communication. This study proposes a novel intensity gradient‐based edge detection (IGED) method for the received pixelated images. In the first stage of the proposed edge detection algorithm, the intensity difference of neighbouring pixels is calculated in the horizontal or vertical direction depending on the presence of a horizontal or vertical edge. In the second stage, the false edge pixels whose intensity values are less than the threshold are removed. Next, slopes are calculated between the consecutive edge pixels and the appropriate lines are found considering the slopes that have almost the same value. The new IGED method performs edge detection without requiring any anchor pixel blocks. This study also provides a description of a misalignment correction algorithm suitable for pixelated images. Next, the effectiveness of the proposed IGED method is tested through an experimental demonstration. It is shown that the IGED method can properly detect the edges even for pixelated images affected by rotational misalignment. For a given transmitter resolution, the proposed method provides better data rates than the existing methods.
Analysis of entrance region flow of Bingham nanofluid in concentric annuli with rotating inner cylinder
Authors: Venthan Selvam Mullai , Amalraj Isaac Jayakaran , Kumar Ponnusamy Senthil
Published: October 2019

This work analyses the entrance region flow of Bingham nanofluids in cylindrical concentric annuli. In this discussion, water is used as the base fluid which is embedded with the silver(Ag) and copper(Cu) nanoparticles coalescing with Bingham fluid. The investigation has been carried out by rotating the inner cylinder, while the outer cylinder is assumed to be at rest. A finite‐difference analysis is used to obtain the axial, radial, tangential velocity components and the pressure along the radial direction. With the Prandtl's boundary layer assumptions, the continuity and momentum equations are solved iteratively using a finite difference method. Computational results are obtained for various non‐Newtonian flow parameters, different volume fraction parameters and geometrical considerations. This work's main interest is to study the development of velocity profiles and pressure drop in the entrance region of the annuli. The present results are compared with the results available in the literature for various particular cases and it is found to be in good agreement.
Properties of LBGs with [OIII] detection at z ∼ 3.5
Authors: Yuan Fang-Ting , Burgarella Denis , Corre David , Buat Veronique , Boquien Médéric , Shen Shiyin
Published: October 2019

Context. Nebular emission lines are critical to measure physical properties in the ionized gas (e.g., metallicity, the star formation rate, or dust attenuation). They also account for a significant fraction of broadband fluxes, in particular at the highest redshifts, and therefore can strongly affect the determination of other physical properties, such as the stellar mass, which are crucial in shaping our understanding of galaxy formation and evolution.

Aims. We investigate a sample of 51 Lyman break galaxies at 3.0 <  zspec <  3.8 with detected [OIII] line emissions and estimated the physical properties of these galaxies to examine the impact of including nebular emission data in the Spectral energy distribution (SED) fitting.

Methods. We used the Code Investigating GALaxy Emission (CIGALE) to fit the rest-frame ultraviolet-to-near-infrared SEDs of these galaxies and their emission line data simultaneously. We ran CIGALE with and without the nebular model or the emission line data, and compare the results to show the importance of including the nebular emission line data in the SED fitting.

Results. We find that without the nebular model, the SED fitting overestimates the stellar mass due to the strong [OIII] lines that are redshifted to the Ks-band, which is consistent with previous results. The emission line data are necessary to constrain the nebular model in the SED fitting. We examine the Ks-band excess, which is mostly used to estimate the emissions of the [OIII]+Hβ lines when there is no spectral data, and we find that the estimation and observation are statistically consistent. However, the difference can reach up to more than 1 dex in some catastrophic cases, which shows the importance of obtaining spectroscopic measurements for these lines. We also estimate the equivalent width of the Hβ absorption and find it negligible compared to the Hβ emission.

Conclusions. Line emission is important to constrain the nebular models and to obtain reliable estimates of the physical properties of galaxies. These data should be taken into account in the SED fitting.