bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation of the Doppler echoes from wind turbine based on scattered electric field calculation
Authors: Tang Bo , Hao Bin , Huang Li , Yang Jiawei
Published: October 2019

Clutter filtering according to distinct Doppler echoes is a major measure to deal with the interference in radar signals caused by the rotating blades of nearby wind turbines. For the problem that the traditional simulation method of scattering point superposition model could not simulate the continuity of induced current on the blade's complex surface, the authors proposed a new simulation method of Doppler echoes based on scattered electric field calculation and expounded the basic principle and implementation steps of the method. First, they found the correspondence between the electric field's complex amplitude vector and the echo signal by deducing the equations of echo signal and scattering electric field; second, they used the quasi‐static technique, the hybrid algorithm of physical optics and method of moment to achieve an accurate solution of the scattered electric field sequence; finally, the authors used the short‐time Fourier transform to obtain the time–frequency domain data of blades Doppler echoes. The result was compared with data obtained from the scattering point superposition model and in‐field experiments, and the accuracy of the proposed method was verified.
Generic aircraft model recognition by two shape factors: in the resonance region
Authors: Aldhubaib Faisal
Published: October 2019

The study utilises two shape factors as the radar feature set for the recognition of a mid‐sized aircraft target in the high‐frequency (HF) band. The two shape factors are the dihedral and tilt features of the aircraft parts. The determination of the two shape factors is feasible through the optimum polarisation states of the target's complex natural resonances in the HF band. The identification algorithm applies a resonance‐weighted measure to the feature set in a supervised learning approach to discriminate between two targets of the same class that slightly differ in shape. The rate of correct recognition within a sector of the target aspect exceeded 80% for receiver sensitivity above −10 dB.
Non‐circular signals for nested array: sum–difference co‐array and direction of arrival estimation algorithm
Authors: Yunfei Wang , Jinqing Shen , Xiaofei Zhang , Yi He , Xiangrui Dai
Published: October 2019

Nested array has aroused remarkable attention due to the capability to obtain both enhanced degrees of freedom (DOFs) and enlarged array aperture, whereas only difference co‐array is employed. Here, the authors construct the sum co‐array of nested array by utilising the non‐circular (NC) characteristic and, subsequently, the sum–difference (SD) co‐array is obtained by careful crafting of the sum co‐array and the typical difference co‐array, which doubles the resulting co‐array aperture and, simultaneously, further increases the achievable DOF compared with the difference co‐array of nested array. Moreover, to circumvent the time‐consuming two‐dimensional spectral search, the authors proposed the reduced‐dimension multiple signals classification (MUSIC) algorithm with the SD (SD‐RD‐MUSIC) co‐array of the nested array by discarding the NC phase. Resultantly, the proposed SD‐RD‐MUSIC co‐array algorithm can resolve more signals and obtain more accurate direction of arrival estimates. In addition, the effectiveness and superiority of the proposed method are validated by numerical simulations.
Doppler effect and micro‐Doppler effect of vortex‐electromagnetic‐wave‐based radar
Authors: Luo Ying , Chen Yi‐Jun , Zhu Yong‐Zhong , Li Wang‐Yang , Zhang Qun
Published: October 2019

The vortex electromagnetic (EM) wave carrying orbital angular momentum (OAM) has attracted much attention in radar applications. Aimed at the moving target detection application of vortex EM waves, the Doppler effect and the micro‐Doppler (m‐D) effect, both including the linear Doppler shift and the angular Doppler shift, are investigated. The theoretical analyses demonstrate that the Doppler effect and the m‐D effect in vortex‐EM‐wave‐based radar are significantly more complicated than those in traditional non‐vortex‐EM‐wave‐based radar, and can provide additional features for target identification and recognition. Simulations are given to validate the proposed theoretical analyses.
Receiver performance and detection statistics of single photon lidar
Authors: Jin Lin , Huang Huixin
Published: October 2019

For a direct‐detection lidar, the use of single photon detector (SPD) could greatly enhance the detection sensitivity of the lidar system. The insufficient SPD in dynamic range limits its application under strong background environment. The authors use the Neyman–Pearson detection theory to analyse the detection performance of single photon lidar under strong noise environment. As a result, the detection statistics can give a basic guide principle for lidar system design. The detection performance is related to input signal‐to‐noise ratio and the number of laser pulses that are integrated over. Furthermore, they analyse the influence of the dual detector AND gate, OR gate, and SUM module on detection performance. The SUM module, namely the SPD array, has the best detection performance. Based on this, a superconducting nanowire single‐photon detector (SNSPD) array‐based lidar is employed for field measurement. The array can make a pre‐processing based on the array data in a single frame. It has a better detection performance for SNSPD array compared with that for single SNSPD.
Clutter map detector for active diver detection sonar
Authors: Delyon Guillaume
Published: October 2019

This study presents a temporal approach based on the clutter map for the automatic detection of divers in the active sonar system. The noisy and non‐stationary surrounding environment of shallow water makes the statistical parameters estimation of classical constant false alarm rate (CFAR) detectors more difficult. In the authors’ system, they take advantage of the fixed positions of the transmitting and receiving arrays in order to improve the statistical parameters estimation over time. The resulting detection algorithm is analysed on simulated data for slow‐moving targets and compared with classical spatial CFAR techniques on real data. The authors show that the proposed technique based on the clutter map provides better results than the classical CFAR techniques, particularly due to a reduction in false alerts. They finally analyse the spatial distribution of false alarms for which randomness is important for the performance of the tracking algorithm. They show that this distribution is more random with the clutter map detector than with classical CFAR techniques.
Real‐time BDS signal‐in‐space anomaly detection method considering receiver anomalies
Authors: Fan Lihong , Tu Rui , Zhang Rui , Zheng Zengji , Liu Jinhai , Hong Ju , Lu Xiaochun
Published: October 2019

Signal‐in‐space user range error (SIS URE) can reach tens of meters or even tens of thousands of meters, and this may introduce hazardous misleading information (HMI) to real‐time navigation and positioning. Monitoring of real‐time SIS anomalies could improve the reliability of navigation and location services for end‐users. For BeiDou satellites, the user range accuracy (URA) index currently broadcasted by navigation ephemeris does not reflect the true variation of URE. The anomaly detection method employed uses priori information from precise ephemerides, remains difficult for real‐time detection. Additionally, the existing SIS anomalies detection method for BeiDou satellites does not exclude the influence of receiver anomalies. To address these problems, a method for calculating the instantaneous URE (IURE) was developed, and the empirical threshold was obtained by statistically analysing IURE before detecting SIS anomalies. Data of 14 stations from the Multi‐GNSS Experiment (MGEX) and the international GNSS Monitoring & Assessment System (iGMAS) in the Asia‐Pacific region were selected for detecting anomalies. Results were analysed in combination with the broadcast ephemeris health status indicator and the precise ephemeris detection results to verify the effectiveness of the method. It shows that the proposed method can accurately detect the starting and ending times of SIS anomalies.
Improving robustness of the MAV yaw angle estimation for low‐cost INS/GPS integration aided with tri‐axial magnetometer calibrated by rotating the ellipsoid model
Authors: Chao Cui , Jiankang Zhao , Hu Jianghao
Published: October 2019

This study designs a method to improve the robustness of the micro air vehicle (MAV) yaw angle estimation for low‐cost inertial navigation system/global positioning system (INS/GPS) integration by using a tri‐axial magnetometer. Observability properties of the integration navigation system are first analysed, indicating that all attitude angles have great observability with the aid of the heading measurement by a magnetometer, while the observability of yaw angle is low in traditional INS/GPS. To improve the robustness of yaw angle estimation, the authors calibrate the tri‐axial magnetometer according to the rotating ellipsoid model and establish a fault detection and isolation mechanism to adjust the weight of magnetic‐measurement adaptively and dynamically in integration navigation. The simulation and experiment results show that the proposed method can calibrate the tri‐axial magnetometer properly and screen out the abnormal magnetic measurement for the robustness of yaw angle estimation, suggesting that this technique is a viable candidate for MAV navigation and control applications in complex magnetic fields.
Accuracy improvement in motion‐measurement using frequency‐weighted Kalman filter
Authors: Shaghaghian Alireza , Karimaghaee Paknoosh
Published: October 2019

Accurate antenna motion‐measurement is an essential pre‐condition for synthetic aperture radar (SAR) to produce well‐focused images. The measurement accuracy at high and low frequencies affects the quality of images and the geolocation error. Hence, motion compensation and focusing techniques require a minimum degree of accuracy in the radar motion measurements. The Inertial Measurement Unit (IMU) sensor selection process is done based on the SAR parametric requirements. The IMU instruments have inherent limited precision and accuracy, which are significantly related to the technology and the cost. The navigation algorithm may improve the precision and accuracy to overcome the limitations of the IMU sensor. This study intends to improve motion measurement accuracy using frequency‐weighted state estimation. The proposed algorithm shows an error reduction in state estimation and an improvement in some parameter indices which are in relation to SAR image quality and geolocation. Two innovative algorithms are proposed in this study. The first one is the frequency‐weighted Kalman filter which is an improved form of the Kalman filter. Another one is multi‐resolution decomposition which is an approach to evaluate the SAR motion measurement system.
Deep neural network‐based Wi‐Fi/pedestrian dead reckoning indoor positioning system using adaptive robust factor graph model
Authors: Wang Yifan , Li Zengke , Gao Jingxiang , Zhao Long
Published: October 2019

A deep neural network (DNN)‐based Wi‐Fi/pedestrian dead reckoning (PDR) indoor positioning system using an adaptive robust factor‐graph model is proposed in this study for the indoor positioning of smartphones. In Wi‐Fi positioning, the authors use a DNN to extract robust features from fluctuant Wi‐Fi signals in the off‐line phase, and obtain more accurate positioning results by computing posterior probabilities in online positioning. Acceleration, gyroscope, and magnetometer data are used to calculate attitude angle, step frequency, and step length, respectively. Received Wi‐Fi signal strength is susceptible in complex indoor environments, and PDR errors accumulate over time. A factor‐graph model with adaptive robust adjustment is proposed to fuse the positioning results of Wi‐Fi and PDR, and it overcomes such shortcomings as slow update frequency and gross errors of Wi‐Fi and PDR errors accumulated over time, respectively. When the absence of PDR occurs, hidden Markov model is introduced to smooth multiple DNN‐based Wi‐Fi positioning estimates at the unknown point to obtain the optimal solution. Experimental results show that the proposed system is more robust and has better accuracy under different motion gestures (held‐in‐hand, dangling, and calling).
End‐to‐end cubic phase signal recovery method based on deep convolutional neural network
Authors: Li Kang , Jiu Bo , Liu Hongwei , Lu Ruiying
Published: October 2019

Cubic phase (CP) signal is widely used in radar and sonar signal processing and the CP signal received by the radar or sonar sensors may miss part of discrete samples and be corrupted by noise. In this study, a novel end‐to‐end CP signal recovery method is proposed to recover the CP signal that experiences data missing and noise corruption based on deep convolutional neural network (DCNN). Two key techniques are used in the structure design of the proposed network. The first is dilated convolution, which has a larger receptive field than the standard convolution operation and can extract information more efficiently in the CP signal recovery problem. The second is denseNet, which connects all layers directly and can alleviate the vanishing‐gradient problem. Experiment results show that the proposed DCNN‐based method achieves superior performance to the traditional compressed sensing‐based method both from the perspective of recovery error and time consumption.
Estimation of HVDC transmission lines shielding failure using LPM method and an adapted SLIM model
Authors: Mohammadi Reza , Vahidi Behrooz , Rahiminejad Abolfazl
Published: October 2019

In this study, the shielding system of HVDC transmission lines against direct lightning strokes is analysed and the shielding failure rate is investigated. The lightning downward leader is modelled using 3D leader progression model (LPM) and the striking point is distinguished employing the self‐consistent upward leader inception and propagation model (SLIM). For determination of striking point more accurately, the required parameters of SLIM model are extracted from the recent experimental results. Different effective objects in the space of study including cloud, lightning channel, towers, wires, and ground are modelled using fictitious charges. Moreover, the charge simulation method is used for electric field calculation. Using the foregoing model, the shielding failure rate of an HVDC transmission line is calculated. Also, the percentages of lightning strokes to each part of the structure are obtained in order to investigate the differences between the positive and negative poles in attracting the lightning. In addition, the effect of height and shielding angles of positive and negative poles are studied. All the results are compared with those of electrogeometric model models.
Electromagnetic transients modelling of split‐winding traction transformers for frequency response analysis
Authors: Sobouti Mohammad Amin , Azizian Davood , Bigdeli Mehdi , Gharehpetian Gevork B.
Published: October 2019

High‐frequency electromagnetic transients modelling of voltage and current distribution due to electromagnetic transients are of great importance in transformer design. In this study, a 2D and 3D finite‐element, coupled field‐circuit and modified detailed model is introduced for high‐frequency electromagnetic transient studies in split‐winding traction transformers. The proposed coupled field‐circuit approach uses a 2D finite‐element model that is coupled with an external circuit to analyse the electromagnetic transient behaviour of the split‐winding traction transformer. Also, a detailed model is introduced for this type of transformer and its results are compared with the introduced coupled field‐circuit model and complete 3D finite‐element model. After validating the introduced models, the models are employed to analyse the frequency response of the split‐winding traction transformer.
Inter‐laminar fault analysis of magnetic cores with grain‐oriented electrical steels under harmonic distortion magnetisations
Authors: Hamzehbahmani Hamed
Published: October 2019

Inter‐laminar faults (ILFs) have major impacts on the overall performance of the electrical machines and power transformers, among which extra power loss and hence lower efficiency could be highlighted. This study presents an in depth analysis on energy loss and energy loss components of stacks of grain‐oriented electrical steels subjected to different kinds of ILFs, under sinusoidal and non‐sinusoidal inductions. Practical methods are developed to monitor quality of the magnetic cores, based on the measured static and dynamic hysteresis loops. The experimental results showed that, ILFs have a significant impact on the dynamic performance and dynamic energy loss of the cores, while their impact on the hysteresis loss is negligible. Furthermore, they become more destructive under non‐sinusoidal inductions, and hence condition monitoring of the magnetic cores is more important for these applications.
Optimising energy in distributed phenomena detection for mobile WSN
Authors: Abu Safia Amany , Kamel Ibrahim , Al Aghbari Zaher
Published: October 2019

We propose an energy‐aware distributed scheme, general phenomena detection, to detect phenomena in data gathered from mobile sensors. In the proposed algorithm, mobile sensors self‐organise themselves into groups and elect group heads (GHs) based on the location of the phenomena. To better share, the extra battery power overhead, GHs and subsequently group membership are updated periodically (every window). Each GH gathers readings from sensors within its group and processes the data to detect possible phenomena within its geographical boundaries. Then, GHs communicate with each other to discover and report global phenomena. To further reduce the energy cost, the study proposes three optimisation strategies: the first strategy, reporting by partial participation (RPP), limits the number of participating GHs in reporting the phenomena. RPP achieved a saving in the energy cost of around 50%. The second strategy, reporting by Z‐order (RZO), provides an overall short communication path between GHs by using Z‐order. RZO achieved a saving of more than 35% of the required energy. The study also proposes a lazy window update strategy that is suitable for a wireless sensor network (WSN) with slow sensor speed. The proposed solutions are validated via comprehensive experiments performed on an NS2 network simulator.
Binary grey wolf optimisation‐based topology control for WSNs
Authors: Ghorpade Sheetal N. , Zennaro Marco , Chaudhari Bharat S.
Published: October 2019

Wireless sensor networks (WSNs) are composed of a large number of sensor nodes that are deployed at target locations. Topology control (TC) is one of the significant fundamental challenges in WSNs because of node energy and computing power constraints. TC algorithms try to produce reduced topology by preserving network connectivity. This study presents a novel TC algorithm based on binary Grey wolf optimisation. It uses the active and inactive schedules of sensor nodes in binary format as well as introduces fitness function to minimise the number of active nodes (ANs) for achieving the target of lifetime expansion of the nodes and network. The proposed algorithm is compared with other TC algorithms. The result reduces a minimum of 10% of ANs and energy consumption by 6.84%. The proposed approach also gives maximum coverage and connectivity. The designed fitness function also benefits in the process of selecting a node with low residual energy to join the active topology. The standard deviation in the remaining energy for the proposed algorithms is lower than the other TC schemes.
Distributed robust filtering with hybrid consensus strategy for sensor networks
Authors: Rastgar Fatemeh , Rahmani Mehdi
Published: October 2019

The problem of distributed state estimation for time‐varying uncertain systems over a sensor network within the robust Kalman filtering framework is studied. It is assumed that the parameters of the underlying model are subjected to stochastic uncertainties. At the first step, the authors present a particular form of the Kalman filter named information form of a robust Kalman filter. Then, using a consensus scheme that guarantees an agreement in estimation among nodes, they propose a new consensus‐based robust filtering approach. The consensus methodology is a hybrid method that is a combination of consensus on information (CI) and consensus on measurement (CM). To this end, before proposing the hybrid consensus filtering algorithm, distributed robust filtering based on CI and CM have been presented. Next, they show that the estimation error in the proposed consensus algorithm is exponentially mean square bounded using a Lyapunov function. Finally, they provide two illustrative examples to show the robust performance and effectiveness of the proposed consensus filtering algorithms.
RTSM: Response time optimisation during switch migration in software‐defined wide area network
Authors: Sahoo Kshira Sagar , Tiwary Mayank , Sahoo Bibhudatta , Mishra Brojo Kishore , RamaSubbaReddy Somula , Luhach Ashish Kr.
Published: October 2019

The distributed control plane is the alternate solution to reliability and scalability like potential issues in the software‐defined wide area network (SDWAN), but the static mapping between controller and switches might cause an uneven load distribution among controllers. Migration of switches from one controller to another under‐loaded controller is a solution to handle the peak traffic. However, the switch migration process is a complex process that may affect the end‐user quality of service (QoS), as a result, the response time of the control messages are also affected. To address this issue, the authors present RTSM, a novel strategy, that optimises the response time of the control messages during switch migration. Further, an SDWAN architecture was proposed, in which the introduction of the layer‐2 controller reduces the dependency on WAN communication of the forwarding devices. The Karush–Kuhn–Tucker conditions have been applied for target controller selection, which ensures improved response time. A switch selection method was also introduced, which minimally affects the end‐user QoS during device migration in SDWAN scenario. To evaluate the performance of the RTSM, Mininet simulator with the Floodlight controller has been used, and the result shows that the proposed algorithm outperforms the other existing works during load balancing.
Low‐loss frequency scanning planar array with hybrid feeding structure for low‐altitude detection radar
Authors: Wang Hao , Zhang Yaodan , Wang Yan , Quan Shuanglong , Xu Dalong
Published: October 2019

A 1 × 4 low‐loss frequency scanning planar array with hybrid feeding structure in Ku‐band has been designed. In order to improve the array efficiency, the planar array was designed by four parallel sub‐arrays and the waveguide slow‐wave line structure with electromagnetic coupled slot on narrow side was used as feed line. The results of simulation show that, except at the centre frequency, the voltage standing wave ratio of the antenna array is below 1.2 at the operation band, the range of the scanning angles is (−30.5°, 29°), the beam width of the antenna is about 5.5°–6.6°, the sidelobe is below −20 dB, and the gain is more than 30 dBi.
PolSAR target scattering interpretation in rotation domain: theory and application
Authors: Chen Si‐Wei , Wang Xue‐Song , Xiao Shun‐Ping
Published: October 2019

The backscattering of radar targets is sensitive to the relative geometry between targets' orientations and the radar. This target scattering diversity makes mechanism interpretation and quantitative application difficult. This study reviews a newly established theory for target scattering mechanism interpretation in the rotation domain. It contains uniform polarimetric matrix rotation theory and the interpretation tool of polarimetric coherence pattern. The core idea of the proposed method is to expand targets' information obtained at a specific orientation to the full rotation domain, which can provide fundamentals for the deep mining and utilisation of target scattering information. On this basis, typical applications with the derived new polarimetric features are introduced and the effectiveness of these features is demonstrated.
Robust method for ship recognition based on ISAR imaging using 3D model
Authors: Xie Sudao D. , Pan M.Y. , Li D.S.
Published: October 2019

This study develops a robust method for ship target recognition, based on inverse synthetic aperture radar (ISAR) image matching with the template of 3D model. To deal with the difficulty of building template lib, the authors develop to use CAD model instead of the live radar data, which can be projected to the range–Doppler plane at any angle. In the study, the method of matching between the observed ISAR image and candidate target image of model is also proposed, including feature extraction and scoring for recognition. In addition, influences of estimation accuracy for projection are analysed and simulated. Finally, recognition results obtained with simulated data are provided to verify the effectiveness of the proposed approach.
Improved receiver autonomous integrity monitoring algorithm
Authors: Li Meina , Hao Zihuan , Zhang Lei
Published: October 2019

The integrity monitoring algorithm guarantees that the receiver can get the correct positioning and speed, which has very important theoretical significance and practical application value. It is one of the most important development contents of the satellite navigation system. Based on the introduction of the traditional least square residual method, this paper compares the binomial fitting time‐assisted receiver autonomous integrity monitoring (RAIM) algorithm and a grey model time‐assisted RAIM algorithm and finds that the latter can well solve the clock error accumulation problem in the binomial fitting time‐assisted RAIM algorithm. In the faulty satellite detection experiments with the same pseudo‐range error, the minimum detectable pseudo‐range error of the grey model time‐assisted RAIM algorithm is 15 m, while the binomial fitting time‐assisted RAIM algorithm is 28 m. Incidentally, the detection probability of a faulty satellite with 20 m pseudo‐range error of the binomial fitting time‐assisted RAIM algorithm is 10%, whereas the grey model time‐assisted RAIM algorithm is 81%.
Research on the method of fast inverse realisation of Vandermonde matrix based on FPGA
Authors: Chen Lei , Chen Liang , Li BingY
Published: October 2019

With the rapid development of science and technology, the operation and calculation in synthetic aperture radar (SAR) imaging systems require high throughput, and the system has high requirement for real‐time performance. At the same time, in the SAR imaging technology, many Vandermonde matrix inversion operations are used in places where the weight coefficients are calculated. Especially when multi‐channel inverse filtering is performed, the use of the Vandermonde matrix inversion operation is a crucial step. In this study, the authors worked hard to find a high speed and accurate Vandermonde matrix inversion algorithm for complex SAR imaging systems. Considering the field‐programmable gate array (FPGA) can be parallel computing and its computing speed is high, the authors chose FPGA to achieve a large number of Vandermonde matrix inversion calculation, and it can meet the requirements of high speed and real time. So, first the realisation method of the fast inversion of the Vandermonde matrix based on Lagrange interpolation polynomial is discussed in this study, which includes pre‐processing module, u matrix calculation module, v matrix calculation module, vector calculation module and post‐processing module. Then, the simulation results of the design are compared and analysed, which proved the correctness and feasibility of the rapid inversion method of Vandermonde matrix.
Modified real‐time sub‐aperture processing algorithm for airborne high‐resolution SAR
Authors: Liu Jing , Chen Hongmeng , Sun Hanwei , Lin Jiahao , Li Congxin
Published: October 2019

The problem of real‐time imaging in synthetic aperture radar (SAR) system is addressed here. Sub‐aperture processing algorithm is usually used in the engineering applications. However, high azimuth sidelobes and edge aliasing problem usually occur in conventional sub‐aperture algorithm, which degenerates the quality of the SAR image. To solve this problem, the reason for high azimuth sidelobes and edge aliasing problem is analysed, and a modified sub‐aperture processing algorithm is proposed. The proposed algorithm minimises the effect of the phase discontinuity to improve the SAR image quality. Therefore, the azimuth sidelobes can be improved, and the edge aliasing phenomenon will be eliminated. Real measured airborne SAR datasets demonstrate the effectiveness of the proposed algorithm.
Multi‐function array SAR system on a spaceborne dual platform
Authors: He Dehua , Zhang Qingjun , Zhu Yu , Zhao Bingji , Lin Qiuhong
Published: October 2019

This study proposes a sparse linear array synthetic aperture radar (LASAR) on a spaceborne dual platform. The transmitting elements are placed at the LASAR tips that form a satellite's dual platform, and the receiving elements are placed on the large deformation composite pine which is between the satellite's dual platform. Based on the principle of phase centre of approximation and multiple input multiple output, LASAR with the sparse array could obtain a high‐resolution imaging in the cross‐along direction, which is crucial to a three‐dimensional SAR system. Furthermore, the LASAR system has different modes, such as interferometry and ground moving target indication.
Measurement of insect mass based on ellipsoid scattering model
Authors: Kong Shaoyang , Wang Rui , Lang Tianjiao , Liu Changjiang
Published: October 2019

Insect migration influences population dynamics, provides ecosystem services, causes heavy crop damages and spreads diseases. The identification of insect migrants is critically important for the study of insect migration. Radar is an effective means of detecting nocturnal insect migrants. The mass, body shape and wingbeat frequency could be measured by the special‐purpose entomological radar. These features are potentially valuable for species identification. This paper proposed a method to extract the mass of migratory insects based on ellipsoid scattering model. This model was used to approximate the small insects in the Rayleigh region, and then the inversion formula of the mass was developed based on ellipsoid scattering characteristics. Finally, through analysing statistical data of insect migrants, the formula was modified to fit small migratory insects. The root mean square percent error is 34.92% for estimates of mass. The given method can promote the species identification and biomass quantification of over‐flying migratory insects, so as to study the role of insect migration in ecosystems and the pest control.
Modelling and quantitative analysis of tropospheric turbulence impacts on GEO SAR imaging
Authors: Hu Cheng , Hu Jiaqi , Dong Xichao , Li Yuanhao
Published: October 2019

Geosynchronous orbit synthetic aperture radar (GEO SAR) has a long synthetic aperture time and a large‐scale imaging scene. Therefore, various non‐ideal factors tend to accumulate, introducing phase errors and decreasing the imaging quality. During the long integration time, troposphere is time varying and space variant, which will result in image shifts and defocusing. According to the characteristics of GEO SAR, this study completes the modelling and the quantitative analysis of tropospheric turbulence. Based on the phase‐screen theory, the amplitude and phase random fluctuations caused by the turbulence which will result in the defocus of images are analysed. However, in the natural environment, the imaging of GEO SAR system is affected weakly by the turbulence and this conclusion is proved from the spectral analysis.
Deformation monitoring of similar material model based on point cloud feature extraction
Authors: Zhou Baoxing , Shan Yuhui , Yao Shoufeng
Published: October 2019

Three‐dimensional (3D) laser scanning technology can reconstruct target models and analyse structural characteristics, and extract complex geometric contents of target structures. Therefore, it is significant to apply 3D laser scanning technology to construct 3D digital models of the monitored objects and to extract their features to judge their movements. This paper presents deformation monitoring method of 3D point cloud based on image information. First, point cloud was first converted into a two‐dimensional intensity image. Topological relations between each point can be determined clearly through the intensity image. Second, based on the wavelet modulus maxima technology, the characteristics of two‐dimensional intensity images are extracted and the corresponding feature point cloud data are obtained. Finally, According to the feature of the point cloud extracted, the change is calculated to determine the deformation of the point cloud object. An experiment was conducted by using a FOCUS3D laser scanner of FARO. The experiment results further verify that the method yields a good effect of deformation monitoring.
Analysis of iridium‐augmented GPS positioning performance
Authors: Xiao Liu , Lei Zhang
Published: October 2019

Although the global positioning system (GPS) has a series of advantages such as global and high precision, there are still many deficiencies, in many cases, GSP cannot meet the requirements of the positioning accuracy. The iridium system is a low‐orbit satellite system with a series of advantages such as global coverage, rapid geometric change, and low propagation loss, which can be combined with the GPS system to achieve the enhancement of positioning accuracy. In this study, the localisation performance of GPS system and iridium‐augmented GPS system is compared using the localisation algorithm based on weighted least‐squares method. The dilution of precision (DOP) values of the GPS system and the iridium‐augmented GPS (iGPS) system and the positioning results before and after the iridium enhancement are calculated. The simulation results show that the iridium augment can optimise the DOP value of the GPS system, reduce the DOP value, and at the same time, when the GPS system cannot get the positioning result, a relatively accurate positioning result can still be obtained through the iridium augment, when the GPS system can get the positioning result, the iridium augment can significantly reduce the positioning error, and can makes the positioning result more accurate.
CNN‐based multiple‐input multiple‐output radar image enhancement method
Authors: Dai Yongpeng , Jin Tian , Song Yongping , Du Hao , Zhao Dizhi
Published: October 2019

In this study, the convolutional neural network (CNN) is utilised to enhance the quality of radar images. First, a four‐layer convolutional neural network is trained. The input of it is a complex valued two‐dimensional low‐resolution radar image, and the output is the radar‐cross‐section distribution image. After processed by the proposed network, the sidelobe and grating lobe in the radar image are suppressed, the main lobe of the target is sharpened. Comparing to the commonly used coherence factor method, the proposed method can enhance the image while maintaining the amplitude scaling relation between targets. The feasibility of the proposed method is testified by both simulated and experimental results.
From Kinect skeleton data to hand gesture recognition with radar
Authors: Li Jiayi , Shrestha Aman , Le Kernec Julien , Fioranelli Francesco
Published: October 2019

In an era where man‐machine interaction increasingly uses remote sensing, gesture recognition through use of the micro‐Doppler (mD) effect is an emerging application which has attracted great interest. It is a sensible solution and here the authors show its potential for detecting aperiodic human movements. In this study, the authors classify ten hand gestures with a set of handcrafted features using simulated mD signatures generated from Kinect skeleton data. Data augmentation in the form of synthetic minority oversampling technique has been applied to create synthetic samples and classified with the support vector machine and K‐nearest neighbour classifier with classification rate of 71.1 and 51% achieved. Finally, using weights generated by an action pair based one vs. one classification layer improves classification accuracy by 24.7 and 28.4%.
Feature clustering based discrimination of ship targets for SAR images
Authors: Ao Wei , Xu Feng , Qian Yutong , Guo Qian
Published: October 2019

Synthetic aperture radar (SAR) is one of the most important and widely‐used tools of large scale marine surveillance. Constant false alarm rate is tailored for maritime metallic target detection in SAR images. However, it is very difficult to distinguish ship targets from other metallic targets. Some manual features have been designed to discriminate ship and non‐ship target. These manual features often overfit some scenarios but fail to other situations. Recently, deep convolutional networks have achieved impressive success in optical image classification, which encourages scholars of remote sensing society to leverage this powerful tool to extract robust features of SAR ship targets. This study adopts VGG‐16 to extract features of ship and non‐ship targets. Then, unsupervised clustering is conducted to group ship and non‐ship targets, respectively, using the extracted features, which can effectively tackle intraspecies variants of ship and non‐ship targets. Finally, these representative feature vectors are utilised to differentiate ship and non‐ship targets of other scenarios. The proposed algorithms are extensively tested undertaken on 11 ALOS‐2 SAR images, which demonstrate good performance of the methods.
Method for high‐resolution SAR imaging based on inverse radon transform
Authors: Wang Zhaofa , Wang Yong , Xu Liang
Published: October 2019

The influence of high‐frequency platform vibration needs to be considered in the synthetic aperture radar (SAR) signal processing, especially at the case that the carrier frequency is in high frequency band. The existence of the vibration will cause the SAR images not to focus. In this study, a novel method for SAR imaging is proposed to enhance the focus performance, where the inverse radon transform based method is employed to estimate the vibration parameters. The effectiveness of the proposed method is verified by simulation results.
Application overview and development trend of passive radar in civil aviation
Authors: Zhang Qiang , Zhang Qingyu , Wu Zhengyuan , Zhao Yixin , Li Hua , Pan Weijun
Published: October 2019

The overall technology of passive radar and application overview in civil aviation are reviewed here, and the research history and status in this field are introduced. It is pointed out that the passive radar has huge application prospects in general aviation surveillance and drone surveillance of the airport terminal area. Then, the key technologies including system synchronisation, reference signal acquisition, weak target signal detection, and single‐frequency network defuzzification are analysed. Finally, the development trends of passive radar are proposed to integrate into existing air traffic management systems, multi‐band integration, and system networking, which indicates the research direction of this new radar system in civil aviation application.
Experimental results of maritime moving target detection based on passive bistatic radar using non‐cooperative radar illuminators
Authors: Jie Song , Fu‐qing Cai , Cai‐sheng Zhang , You He
Published: October 2019

A signal processing method of passive bistatic radar using non‐cooperative pulse radar illuminators is proposed. The proposed method estimates unknown parameters of transmitting radar signal from direct‐path signal, and uses estimated parameters for coherent processing a series of pulses and positioning the detected maritime moving targets correctly in a 2D radar map, and to calculate the azimuth, bistatic range and Doppler frequency of targets. The experiments use the shore‐based maritime surveillance radar as a non‐cooperative transmitter and ships coming in and out from the seaport as the targets, which show that the proposed method can be applied to maritime moving target detection successfully.
Quantum detection theory and optimum strategy in quantum radar system
Authors: Zhao Sheng‐Zhi
Published: October 2019

As new concept radar combing quantum technology with radar technology, quantum radar is an extension of traditional radar theory and has the potential to break through the limit of conventional radar detection performance. We study quantum radar optimum decision strategies for various signal and background forms and compare them with traditional photon‐counting strategies. Quantum optimum strategy gives better detection probability with fixed false‐alarm probability, thus reducing needed signal strength to detect the target, but its validity strongly depends on exact knowledge of signal forms. We briefly discuss the influence of deviating signal amplitudes and phases, and find that in the condition that the false‐alarm probability is very small quantum optimum strategy is still useful when the signal form varies in a small region.
Long‐time coherent accumulation algorithm based on acceleration blind estimation
Authors: Wang Zhuo , Zheng Xuehe , Chang Xiaolan
Published: October 2019

Aiming at the limitation of the coherent accumulation gain of the air defence missile active radar seeker, which is brought by a new generation of manoeuvrable stealth targets, this study proposes a long‐time coherent accumulation algorithm based on the blind estimation of relative acceleration between missile and target, which is suitable for the pulse Doppler seeker. By extracting the relative acceleration information carried in the echo signal, the algorithm compensates the original echo signal phase, so that the compensated signal can be refocused in the frequency domain and the seeker detection capability to the large manoeuvring target can be improved. The simulation results show that the seeker sensitivity can be increased by 8 dB when the system false alarm probability is <10−7 and the intercept probability is >0.99.
Using integer and fractional measure for processing and recognitions of small and distorted images in optical location and medicine
Authors: Potapov Alexander A. , German Vitaly A. , Pakhomov Andrey A. , Grachev Vladimir I. , Zhang Wei , Feng Tianhua
Published: October 2019

The present work develops the mathematical base of ill‐posed inverse problems in optics, as well as a method of processing and reconstructing scenes from incomplete information of their Fourier spectra. This problem is a part of the general problem of the eliminating the influence atmospheric and optical distortion when finding and registering an object at large distances under bad atmospheric conditions. The designed programmed methods are also used to process medical images.
Efficiency balanced matrix transpose method for sliding spotlight SAR imaging processing
Authors: Sun Tianyuan , Xie Yizhuang , Li Bingyi
Published: October 2019

Matrix transposition is a very critical operation in synthetic aperture radar (SAR) imaging systems. This study presents an improved corner turning memory solution for real‐time SAR imaging processing. Based on the sub‐matrix three‐dimensional mapping method, the efficiency of matrix transposing is greatly increased. However, in sliding spotlight mode, a novel SAR imaging mode, the amount of raw data is increased too large to directly use the above method. In this study, a joint address mapping strategy for two pieces of double data rate 3 synchronous dynamic random‐access memory is used to meet the needs of the amount of data and make up for the lack of original method. The experimental results show that this method can get an improved and balanced two‐dimensional access efficiency for sliding spotlight mode SAR imaging processing.
Experimental validations of insect orientation extraction based on fully polarimetric measurement
Authors: Li Weidong , Hu Cheng , Wang Rui , Liu Changjiang , Li Wenqing
Published: October 2019

The purpose of this study is to demonstrate that the fully polarimetric radar can be effectively used to measure the insect orientation. First, the polarisation scattering matrix (PSM)‐based orientation extraction method is reviewed. This method was proposed for traditional rotation polarisation radar, but is also applicable to fully polarimetric radar. Then, both anechoic chamber and field experiments were conducted to measure fully polarimetric insect PSMs and orientations, which verified the effectiveness of insect orientation extraction based on fully polarimetric measurement.
Lateral velocity measurement and error analysis
Authors: Qiang Mengye , Bai Yechao , Zhang Xinggan
Published: October 2019

Most existing velocity measurement methods can only calculate the radial velocity by Doppler effect. Here, the authors study the method of measuring the lateral velocity. It is found that the lateral velocity influences the changing rate of Doppler frequency over time, which inspires them to measure the lateral velocity by analysing the Doppler spectrum or the quadratic phase of the echo. The relationship between the echoes and the lateral velocity is modelled in this study. Also the mean square error of lateral velocity measurement, including the model error and the estimation error, is also deduced. The influence of the observation time is studied according to the mean square error.
Visualisation and interpretation of PolSAR data based on polarimetric coherence
Authors: Liang Liting , Zhang Yunhua , Li Dong
Published: October 2019

Polarimetric coherence strongly relates to the target scattering characteristics. Coherences of different second‐order statistics show different advantages in target discrimination in specific correspondence to physical scattering mechanism. A fast visualisation scheme of the coherency matrix and circular polarisation covariance matrix is developed by adopting the polarimetric coherence for the interpretation of polarimetric synthetic aperture radar (PolSAR) data. The scheme has much less computational burden compared with other decomposition and classification algorithms. It can be regarded as a basic operation of PolSAR data as the Pauli decomposition. Its strong relationship with polarimetric scattering entropy is revealed which substantiates the efficacy in terrain classification. The performance and advantages of the scheme are demonstrated on airborne synthetic aperture radar (AIRSAR) and Electromagnetics Institute synthetic aperture radar (EMISAR) datasets.
Deep forest for radar HRRP recognition
Authors: Wang Yanhua , Bi Xuejie , Chen Wei , Li Yang , Chen Qiao , Long Teng
Published: October 2019

High‐resolution range profile (HRRP) has received intensive attention in the radar automatic target recognition filed. Here, deep forest is applied to the recognition of HRRP. The deep forest is a deep learning method, which is a cascade of ensemble learners. In each layer, there are various ensemble learners. The input of each layer is the combination of the previous layer output and the original input data. The number of cascade levels can be adaptively determined such that the model complexity can be automatically set. Experiments based on measured data show that deep forest is feasible and achieves highly competitive performance for HRRP recognition.