bluuebunny/crossref_metadata_2025 huggingface dataset:
Spaceborne synthetic aperture radar imaging mapping methodology based on FPGA‐DSP hybrid heterogeneous architecture
Authors: Yu Wenyue , Xie Yizhuang , Li Bingyi , Chen He , Liu Xiaoning
Published: October 2019

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data bring challenges for high‐speed transmission and real‐time processing. The general platform with GPU, CPU or digital signal processor (DSP) cannot meet the requirement for short delay and low power. Therefore, a field‐programmable gate array‐digital signal processor (FPGA‐DSP) SAR imaging accelerate platform has become a solution for processing performance with a lower latency and power. In this study, an effective mapping strategy is adopted to the FPGA‐DSP hybrid heterogeneous architecture to accelerate the processing performance according to the analysis of Chirp Scaling SAR imaging algorithms. As a proof of concept, a FPGA‐DSP hybrid heterogeneous accelerating platform is designed and realised. The platform requires 12 s to focus a stripmap SAR raw data with a granularity of 16,384 × 16,384.
Track‐before‐detect algorithm for airborne radar system
Authors: Wang Yaru , Wang Jinghe , Wen Ming , Yi Wei , Kong Lingjiang
Published: October 2019

This study considers the detection of dim target via track‐before‐detect (TBD) in airborne radar system. Dim target detection by TBD is well‐studied while aircraft ego‐motion is not taken into account. Ego‐motion of the aircraft (platform) causes traditional TBD method useless in airborne radar system by two reasons. On one hand, the movement of the aircraft causes measurement misaligned among different frames. On the other hand, state space and measurement space is non‐one‐to‐one correspondence. Considering these two issues, the authors proposed a TBD algorithm for airborne radar based on plots (AR‐P‐TBD). First, they derived coordinate rotation and motion compensation formula, and convert each frame of measurement into a unified coordinate system to make these measurements aligned. Then, TBD processing in measurement space is implemented. It avoids the non‐one‐to‐one correspondence between state space and measurement space. Simulation results demonstrate the effectiveness of AR‐P‐TBD.
Long‐term tracking with fast scale estimation and efficient re‐detection
Authors: Zengshuo Zhang , Linbo Tang , Yuqi Han , Jinghong Nan , Baojun Zhao
Published: October 2019

In long‐term tracking applications, occlusion and scale variation are common attributes which cause performance degradation. Existing solutions use heavy calculation to deal with these problems, without considering the real‐time implementation. Therefore, the authors propose a novel long‐term tracker with fast scale estimation and efficient re‐detection scheme to maintain real‐time speed and favourable accuracy. Specifically, the authors integrate a distance metric method into correlation filter‐based tracker to realise fast translation calculation and scale estimation. In addition, the authors advocate a keypoint‐matching based confidence indicator to verify the tracking result and activate the re‐detection module when the occlusion happens. The authors test our approach on challenging sequences with scale variation and occlusion. Experiments demonstrate that our proposed tracker procures preferable effect than state‐of‐the‐art methods in the aspect of both speed and accuracy.
SAR image denoising method based on sparse representation
Authors: Zhou Hao‐Tian , Chen Liang , Fu Bo , Shi Hao
Published: October 2019

The coherent nature of radar illumination causes the speckle effect, which gives the synthetic aperture radar (SAR) image its noisy appearance. The probability distribution of speckle noise is multiplicative rather than additive, which makes the interpretation and processing of SAR imagery more difficult. A novel SAR image denoising method is proposed. First the multiplicative noise is transformed into additive‐like noise by logarithmic transformation. After that, a novel object function is proposed which combines a pre‐trained dictionary model to deal with the image. Finally, exponential transform is employed to recover the image. Experimental results show that the proposed method can effectively remove the noise of SAR images, and indicate good performance compared with other state‐of‐the‐art methods.
Building extraction from GF‐3 images using Wishart classification assisted by extended volume scattering model
Authors: Zheng Changli , Ding Qing , Zhang Wei , Luo Jinghui , Wang Xiaoxia
Published: October 2019

Building extraction is considered as one of the primary applications of urban remote‐sensing. To address the misclassification issue on building extraction based on Yamaguchi decomposition, an extended volume scattering model‐assisted building extraction method is proposed. Here, the HV components caused by buildings whose main surface are oriented with respect to radar beam are assigned to double bounce scattering, since the extended volume scattering model is introduced. On this basis, the complex Wishart iterative classification is introduced to develop a new method of building extraction. The proposed method is employed to process C‐band full‐polarimetric SAR imagery obtained by GF‐3. The study results verify the efficiency and accuracy of proposed method.
Extraction method of wide‐band phased array radar signals based on pulse amplitude characteristic
Authors: Xianghao Meng , Yongwang An , Pengyong Li
Published: October 2019

Wide‐band phased array radar is the primary focus in electronic countermeasure reconnaissance, and prior extraction of such radar signals in the interleaved pulse data intercepted by the receiver has important military significance. Aiming at full pulse data intercepted by the receiver, a prior extraction method of wide‐band phased array radar signals is proposed in this study. Utilising the electronic scanning feature of wide‐band phased array radar, analyse the unchanging characteristic of pulse amplitude under the same working mode, and combine the pulse width characteristics of wideband pulse, a dichotomising reasoning algorithm in bioinformatics is introduced in this study. Firstly, reorder the full pulse data, filtrated by pulse width threshold, according to pulse amplitude; then, test the discontinuity points of pulse amplitude by employing the dichotomising reasoning algorithm, dividing the pulse sequences into segments with the same pulse amplitude; lastly, conduct pulse number threshold filtering on every segment, realising the extraction of wide‐band phased array radar signals. The validity of this method has been verified by simulation experiments.
Doppler compensation method for the complementary phase‐coded signal
Authors: Li Wenji , Ren Lixiang , Mao Erke , Fan Huayu
Published: October 2019

The Doppler sensitivity issue is an urgent problem to be solved for the phase‐coded radar although it can give the promise of improved range resolution and resistance against various kinds of distortion. Due to the ideal autocorrelation and cross‐correlation properties, the complementary sequence is utilised in high‐frequency surface wave radar and MIMO radar. However, the Doppler frequency shift affects the autocorrelation property of the complementary sequence. This study aims to solve this problem. Based on the signal model and mathematical derivation, a new algorithm is proposed and the simulation results indicate the effectiveness of this method. This study also puts forward the signal processing diagram and the method to obtain the new code.
Training sample selection for space–time adaptive processing based on multi‐frames
Authors: Zhang Chenxiao , Wu Yifeng , Guo Mingming , Deng Xiaobo
Published: October 2019

As training samples are not identically distributed with cell under test (CUT) in heterogeneous environments, the performance of space–time adaptive processing (STAP) to suppress clutter degrades. To improve the performance of STAP, this study proposes a novel training sample selection method for STAP based on multi‐frames. The key feature of the new method is to overcome the deficit of independent and identically distributed (IID) training samples in heterogeneous environments. First, multi‐frames are selected according to similarity from continuous frames; second, training samples which are IID to the CUT from current frame are selected; finally, combine the training samples of the current frame and same range samples in reference frame into final training sample set. The proposed method is applied to real‐radar data, and experimental results demonstrate the effectiveness of the proposed method.
Analysis of phase noise influence on micro‐Doppler feature extraction of vibrating target
Authors: Liu Zihao , Peng Bo , Li Xiang
Published: October 2019

It is generally considered that increasing the carrier frequency of radar is an important way to improve the precision of micro‐motion measurement. However, the increase of the radar frequency may raise the phase noise intensity of the radar transmitting signal and make the extraction more difficult, therefore it is particularly necessary to study the influence of phase noise on the extraction of micro‐motion characteristics. In this study, specific studying about the effect of phase noise on the extraction of micro‐Doppler (m‐D) features is carried out. The effect of phase noise on the extraction performance of the m‐D features is evaluated based on a parameter micro‐motion signal‐to‐clutter ratio and an empirical formula is put forward based on the experiments. The results of simulation experiments indicate that increasing the carrier frequency cannot improve the extraction performance of micro‐motion features in the case of using both time–frequency analysis method and the new developed sinusoidal frequency modulation Fourier transform (SFMFT) method. Meanwhile, increasing the frequency of target's micro‐motion has an improvement effect through time–frequency method due to the increase of Doppler frequency.
Prospects of FMCW‐based frequency diverse array radar
Authors: Çetiner Ramazan , Çetintepe Çağrı , Demir Şimşek , Hizal Altunkan
Published: October 2019

The linear frequency modulated (LFM) frequency modulated continuous wave (FMCW)‐based frequency diverse array (FDA) radar concept is investigated in detail. The radar operates as a linear pulsed FMCW/FDA in the transmission (TX) mode while it operates as a pulsed FMCW/phased array (PA) in the receiving mode. The issues such as low signal‐to‐noise ratio (SNR) of FDA, the time‐angle scanning and time‐range ambiguities are studied. It is shown that the local instantaneous frequency bandwidth is much smaller than the radio frequency (RF) deviation of LFM. Positive and negative slope TX/RF locations offer frequency diversity. Time domain and frequency domain signal processings are described. A Ku band direct digital synthesis‐based FMCW/FDA radar example based on the cumulative detection scheme is given and compared with an equivalent FMCW/PA radar.
Novel radar signal to efficiently utilise spectrum based on continuous‐phase frequency‐shift keying
Authors: Jie Zhang , Xuewei Xu , Tao Jiang , Hong Zhang
Published: October 2019

Aiming at the problem of high side‐band spectrum for a general frequency‐shift keying (FSK) radar signal, this study introduces a novel radar FSK signal based on continuous‐phase frequency‐shift keying (CPFSK) used in communication systems. Theoretical analysis, simulation and physical application results show that the CPFSK radar signal efficiently controls the spectral containment, whose roll‐off performance of the CPFSK is ∼20 dB better than that of normal FSK; meanwhile, the modified signal possesses good ambiguity and pulse compression performances for radar application.
Method for automatically identifying PRI patterns of complex radar signals
Authors: Tang Yuwen , He Minghao , Tang Xiaojie , Han Jun , Fan Xikun
Published: October 2019

Aimed at the problem of automatically identifying pulse repetition interval (PRI) patterns of complex radar signals, a novel method is proposed in this paper. The roughness, normalised mean jump energy, and Sp‐ curve characteristic are extracted as feature set based on the analysis of PRI sequences in time domain. Finally, the decision tree is employed to recognise different PRI patterns. The simulation results show that the algorithm has high recognition accuracy and good robustness to spurious pulses and pulse missing.
Simulating multi‐fractal sea clutter and surface based on the random multiplicative model
Authors: Xi Caiping , Xiong Gang , Yang Yonghong , Chen Si
Published: October 2019

It has been proved that the multi‐fractal sea clutter can be simulated by the three‐partitioned random multiplicative model. This study constructs multi‐fractal sequences with similar multiplicative factors of the sea clutter of the IPIX radar and calculates the multi‐fractal spectra by the Q th‐order moment structure partition function. Simulation results prove that it can construct multi‐fractal sequence with the multi‐fractal spectrum similar to the given one. Then the N 2 ‐partitioned random multiplicative model is proposed to simulate the two‐dimensional surface and calculate the multi‐fractal spectrum by the two‐dimensional multi‐fractal analysis based on the partition function approach. Simulations indicate that it is a good way to simulate the multi‐fractal surface based on the N 2 ‐partitioned random multiplicative process model. It provides a new way for the surface modelling of the sea surface.
Fast target deception jamming method against spaceborne synthetic aperture radar based on equivalent bistatic scattered fields
Authors: Sun Qingyang , Shu Ting , Yu Kai‐Bor , Yu Wenxian
Published: October 2019

To achieve verisimilar target deceptive jamming effect, the jamming signals from different targets in different kinds of situation must be acquired. However, it is difficult to be implemented by the methods using deception‐template model. In this letter, a novel target deception jamming method against spaceborne synthetic aperture radar based on electromagnetic (EM) simulation is presented. To improve the computational efficiency, an equivalent bistatic scattered fields are used to simulate the scattering characteristics of false target. The proposed method, which consists of the computer‐aided‐design model, the deceptive jamming model and the involved EM scattered fields, improves the performance of deceptive target in achieving the jamming results. The simulation results demonstrate the validity of the proposed method.
Decorrelation in GEO SARs due to radio frequency interferences
Authors: Li Yuanhao , Guarnieri Andrea Monti , Hu Cheng
Published: October 2019

Geosynchronous synthetic aperture radar (GEO SAR) is a very remarkable tool for monitoring rapid geologic disasters due to its short revisit time and long coverage time for targets. However, its large swath makes the system easily impacted by radio frequency interferences (RFIs), which can cause the decorrelations in images and interferograms. In this study, the authors establish the RFI decorrelation model in GEO SARs based on the signal‐to‐interference‐plus‐noise ratio analysis. Moreover, the mitigation method for RFI decorrelation based on proper system parameters design is proposed. Finally, simulations are conducted to evaluate the RFI decorrelations under different target types and orbits, and the corresponding required system parameters for mitigation are analysed as well.
Fractals, scaling, textures, fractional operators and deterministic chaos as the physical and mathematical components of the new conceptions and methods in radar and radio physics
Authors: Potapov Alexander A.
Published: October 2019

Main results of theoretical and experimental investigations since the 1980s of 20th century that led to the formation and developing of new fundamental science discipline: ‘Fractal Radio Physics and Fractal Radio Electronics: Fractal Radio Systems Designing’ are briefly classified in the study.
Moving target detection based on velocity compensation methods in a coherent continuous wave lidar
Authors: Huang Huixin , Xu Chi , Xia Linghao , Wu Cheng
Published: October 2019

Light Detection and Ranging (lidar) technology has been applied in military and civil areas and shows great potential. However, in coherent lidar detection, significant Doppler Effect and velocity uncertainty result a bad influence on moving target ranging. In this study, the authors demonstrate a velocity compensation method based on both Doppler shift evaluation and velocity searching and matching method. The authors used dot‐linear frequency modulation signal for detection in order to achieve both velocity and distance information in the same period. Further by using searching and matching processing based on Shannon entropy can give a better‐compensated velocity to extract more accurate distance information of targets. The authors applied this method on passive and self‐driving moving targets, which fit the actual characteristics of both kinds of targets. Especially in self‐driving moving target, there exists a significant target fluctuation in movement during detection that causes the splitting of Doppler peaks. The blurry in velocity estimation restricts the accuracy of sensing. The authors found the Shannon entropy searching method could reduce this effect. On the other hand, the feature of fluctuation in micro movement may give a way to identify the targets in the future.
Cycle‐slip detection and correction of GPS single‐frequency carrier phase based on wavelet transform and LS‐SVM
Authors: Tu Xu , Lei Zhang
Published: October 2019

The high‐precision positioning of GPS requires to detect and correct the cycle‐slips in carrier phase more accurately and efficiently. In order to improve the ability of GPS single‐frequency receivers to detect and correct small cycle‐slips, the reason for the occurrence of cycle‐slips and the principle of their detection and correction are analysed; then, a method of GPS single‐frequency receivers' cycle‐slip detection and correction based on wavelet transformation and LS‐SVM is proposed. Here, WT is used to locate the cycle‐slip and the LS‐SVM is used to determine the value of it and correct it. The simulation results show that this method can detect and correct up to one cycle‐slip accurately but in contrast, the traditional polynomial fitting method can only detect and correct at least two cycle‐slips in the same condition. The feasibility of this method and its ability to accurately correct small cycle‐slips are demonstrated.
Study on propagation characteristics of laser in turbulent Rayleigh–Bénard thermal convection
Authors: Zhou Zhichao , Liu Kang , Xu Lingfei , Zhang Guangjun , Wang Zhe , Ren Tianrong , Gu Cunfeng , Sun Gang
Published: October 2019

The turbulent Rayleigh–Bénard (R–B) convection system contains the plume and the large‐scale circulation structure, which causes the statistical inhomogeneity of the flow field. The high coherence of the laser leads to the completely different transmission characteristics in the R–B flow field than in the free space. In this study, the transient scattering field of the laser in the R–B flow field is calculated by using the Maxwell numerical integration method under the Rytov approximation. The experimental device was designed, the comparison experiment was carried out, and several satisfactory contrast results were given.
Cognitive HF radar
Authors: Anderson Stuart
Published: October 2019

Radars operating in the high‐frequency (HF) band can exploit propagation modes other than line‐of‐sight and are hence widely employed to provide over‐the‐horizon surveillance and remote sensing. Most HF radars operating today rely on surface wave propagation; while opportunities for enhancing their performance by adding cognitive features exist, these have not been widely seized. In contrast, designers of HF skywave radars, which exploit ionospheric reflection to achieve ranges in excess of 4000 km, have long sought to counter the enormous challenges of the geophysical environment by implementing schemes to raise radar intelligence quotient (IQ) and autonomy. Measures that have been explored relate to resource allocation, operating procedures, signal processing, target classification and remote sensing. The perception–action cycle constitutes the structural element of these developments, accessing prior knowledge and input from auxiliary sensors, exactly as proposed by those who later coined the term cognitive radar. Here, the roles of cognition in HF skywave radars are reviewed, illustrating the needs and benefits with examples including detection in sea clutter, ionospheric channel compensation and multiple‐input and multiple‐output HF radar.
Correlation‐matching multipath suppression algorithm in three‐dimensional through‐wall radar imaging
Authors: Lingxiao Cao , Guolong Cui , Yilin Song , Shisheng Guo , Lingjiang Kong
Published: October 2019

The interference of the multipath spreading among the targets and the interior walls will be introduced into the radar image. This study mainly deals with the multipath suppression problem in three‐dimensional (3D) through‐the‐wall radar imaging. The authors propose a correlation‐matching multipath suppression algorithm to eliminate the first‐order back wall multipath ghosts. Specifically, they first extract the barycentre coordinates of all objects in the original radar image. Second, a decision criterion is provided to measure the relevance between these objects. If two objects are closely related, they assert that they have multipath‐target relationship. Finally, they eliminate the multipath ghosts after all objects being determined. At the analysis stage, they assess the effectiveness of the proposed approach through simulation results, which shows its ability of well‐removing multipath ghosts.
FMCW radar and inertial sensing synergy for assisted living
Authors: Li Haobo , Shrestha Aman , Fioranelli Francesco , Le Kernec Julien , Heidari Hadi
Published: October 2019

This study presents preliminary results about the multi‐sensory recognition of indoor daily activities and fall detection, to monitor the well‐being of older people at risk of physical and cognitive chronic health conditions. Five different sensors, continuous wave (CW) radar, frequency‐modulated CW (FMCW) radar, and inertial measurement unit comprising an accelerometer, gyroscope, and magnetometer were used to simultaneously collect data from 20 subjects performing 10 activities. Rather than using all of the available sensors, it is more efficient and economical to select part of them to maximise the classification accuracy and avoid unnecessary computation to process information if it is not salient. Each individual sensor and several sensor combinations are trained with a quadratic‐kernel support vector machine classifier. In addition, they are validated with an improved statistical approach, which uses data from unknown participants to test model rather than random cross‐validation to verify if the model generalises well for unknown subjects. Furthermore, the most suitable sensor combinations are derived for each specific group of tested subjects selected (e.g. the oldest, youngest, tallest, and shortest sub‐groups of participants out of the entire group).
Elderly care: activities of daily living classification with an S band radar
Authors: Shrestha Aman , Le Kernec Julien , Fioranelli Francesco , Lin Yier , He Qian , Lorandel Jordane , Romain Olivier
Published: October 2019

Falls in the elderly represent a serious challenge for the global population. To address it, monitoring of daily living has been suggested, with radar emerging to be a useful platform for it due to its various benefits with acceptance and privacy. Here, we show results from the use of an S band radar for activity detection and the importance of selecting specific frequency bins to improve its suitability for human movement classification. The use of feature selection to improve detection of key activities such as falls has been presented. Initial results of 65% are improved to 85% and further to 90% with the aforementioned methods.
Design of terahertz frequency scanning reflector antenna and its application in direction‐of‐arrival estimation
Authors: Li Shichao , Hou Peipei , Zhang Pengcheng , Hao Congjing , Qu Jian , Jia Qu , Li Gang , Li Chao
Published: October 2019

A novel frequency scanning‐based direction‐of‐arrival (DOA) estimation scheme is proposed at terahertz (THz) band. The diffraction enhancement mechanism, focusing the superposition of the diffracted beam radiated from each element in one unit cell, is expanded to the 0.3 THz band. The frequency scanning reflector antenna (FSRA) operating at 235–330 GHz is proposed with high diffraction efficiency. Angular super‐resolution algorithm is proposed based on the FSRA. Maximum likelihood (ML) method, traditionally used in array signal processing, is extended to the novel frequency scanning system based on the FSRA. The model of FSRA manifold vector is constructed. A FSRA operating on 0.3 THz frequency band was experimented, based on which the DOA estimation system is constructed. The resolution of the frequency scanning ML algorithm can be obtained on the level of half of the 3 dB beamwidth by the proof‐of‐principle experiments in 0.3 THz band.
Adaptive convolutional network for SAR image classification
Authors: Xia Shuang , Yu Ze , Yu JinDong
Published: October 2019

Convolutional neural network (CNN) has an outstanding performance in image classification via extracting highly effective features automatically. However, when CNN is applied to target recognition of synthetic aperture radar (SAR) images, overfitting problem exists since the lack of sufficient labelled SAR images. Hence, based on the moving and stationary target acquisition and recognition (MSTAR) benchmark dataset, the authors proposed the Adaptive‐Convnet, it has a strong generalisation ability and has a good performance in different testing conditions. Besides, they also studied the transfer learning method to transfer knowledge learned from simulated SAR data to real SAR image recognition, to achieve the purpose of expanding the data set at low cost. When they substitute a part of real T72 images from MSTAR with more simulated T72 SAR images and reduce the dataset bias and enhance transferability in the last three convolution layers, the classification accuracy improved.
Synthetic aperture radar target recognition of incomplete training datasets via Siamese network
Authors: Tang Jiaxin , Zhang Fan , Yin Qiang , Hu Wei
Published: October 2019

Synthetic aperture radar (SAR) target recognition can provide effective target category information and becomes the key part of SAR image application. Machine learning and deep learning are two main methods of target recognition. Normally, through the massive image features learning, the trained model can be used to infer the possible categories for various new target images, but the overfitting problem caused by limited data samples always makes the trained model unusable. In order to solve this case, the authors introduce a dual‐input Siamese convolution neural network to the small samples oriented SAR target recognition. The training method looks like a kind of data enhancement method, but there are some differences between them. In the experiments, only 15 training samples are used to complete a three‐class tank classification task. It means each category has just five samples while the number of corresponding testing data is 195. As a result, the recognition accuracy of the authors’ method outperforms the support vector machine, A‐ConvNet, and 18‐layers ResNet by 31, 13 and 16%, respectively. Siamese network has a good performance in small samples classification and the results prove the validity of the network.
Efficient deep convolutional neural networks using CReLU for ATR with limited SAR images
Authors: Wang Zelong , Xu Xianghui
Published: October 2019

The computational cost of many deep convolutional neural networks (CNNs) for the automatic target recognition proposed in the area of synthetic aperture radar (SAR) imagery recently is huge, and the limited SAR images are always insufficient for training the deep CNNs. To improve the computational efficiency, a new light but very efficient convolutional network architecture is designed using some novel techniques to get the better results. The authors apply the batch normalisation before each convolutional layer in order to reduce ‘internal covariate shift’ and use the drop‐out strategy in the fully layer to avoid over‐fitting. Additionally, concatenated ReLU is used as activation scheme specially instead of ReLU for preserving the negative phase information to get the double feature maps of the previous layer rather than to increase the depth of the filters that can lessen the parameters of the networks. The results of the experimental demonstrate that the authors’ CNNs can both achieve a state‐of‐the‐art classification accuracy of 99.53% of the SAR target classification in the Moving and Stationary Target Acquisition and Recognition ten classes public dataset and perform well even when the training data is sparse.
Multi‐task fully convolutional networks for building segmentation on SAR image
Authors: Zhang Zenghui , Guo Weiwei , Yu Wenhao , Yu Wenxian
Published: October 2019

Fully convolutional networks (FCN) and related advanced variants have attached outstanding performance on optical image semantic segmentation. However, they do not obtain similar performance gain on synthetic aperture radar (SAR) image if they are directly applied due to the differences between optical and SAR images. The missing alarm rate of FCN remains high for some building targets. In this study, a multi‐task FCN is proposed for building extraction from SAR images. The main task remains the same as the original FCN, and in addition, a branched sub‐task is designed to extract the pivotal parts of buildings to make the entire networks pay more attention to the high backscattering intensity parts of buildings. The main network then can be boosted by the related sub‐task and reduce the missing rate. The experimental results on the same data set show that this model reaches low missing rate and demonstrate the efficiency especially for some particular buildings targets.
Three‐dimensional ISAR imaging: a review
Authors: Martorella Marco , Salvetti Federica , Staglianò Daniele , Giusti Elisa
Published: October 2019

Three‐dimensional (3D) inverse synthetic aperture radar (ISAR) imaging has been proven feasible by combining traditional ISAR imaging and interferometry. Such technique, namely inteferometric ISAR (In‐ISAR), allows for the main target scattering centres to be mapped into a 3D spatial domain as point clouds. Specifically, the use of an In‐ISAR system can overcome the main geometrical interpretation issues imposed by the monostatic acquisition geometry as the problem of cross‐range scaling and unknown image projection plane (IPP). However, some issues remain such as scatterer scintillation, shadowing effects, poor SNR etc., which limit the effectiveness of 3D imaging. A solution to such unsolved issues can be found in the use of multiple 3D views, which can be obtained exploiting either multi‐temporal or multi‐perspective configurations or a combination of both. This study aims to review the main concepts to produce multi‐view 3D ISAR images by using In‐ISAR systems also presenting real data collected with a multi‐static In‐ISAR system.
Compressive sensing approach for high‐resolution ISAR image reconstruction and autofocus
Authors: Kang Min‐Seok , Kim Kyung‐Tae
Published: October 2019

In this study, a novel autofocus method is presented to achieve high‐resolution inverse synthetic aperture radar (ISAR) image reconstruction with limited measurements in the compressive sensing (CS) framework. In order to solve the CS reconstruction problem of ISAR images with sparsity, the CS coupled with Tikhonov‐regularisation‐based algorithm is devised as an effective focusing technique. The proposed method aims at compensating the phase errors induced by target motions, and can provide globally well‐focused ISAR images. Simulation and experimental results verify the effectiveness of the proposed scheme.
LTE‐based passive radar for drone detection and its experimental results
Authors: Dan Yangpeng , Yi Jianxin , Wan Xianrong , Rao Yunhua , Wang Benjing
Published: October 2019

To satisfy growing demands of detection of illegally used drones, this study has investigated the feasibility of drone detection by passive radar exploiting wide available long‐term evolution (LTE) downlink signal. Based on the software‐defined radio concept, Wuhan University has independently developed a LTE‐based passive radar system. Agreements in preliminary experimental results and ground truth verify the effectiveness and practicability of such system, which indicates the potential and prospects of drone detection by LTE‐based passive radar.
Mainlobe interference cancellation based on PCA + ECA in passive bistatic radar
Authors: Gao Bo , Guo Shuai , Wang Jue , Wang Jun , Lou Baofang , Yan Yifei
Published: October 2019

The mainlobe interference is a noticeable issue in the passive bistatic radar. As the direction of arrival (DOA) of the interference is close to the DOA of the target echo, the interference hardly be cancelled by the adaptive spatial filtering. After clutter cancellation, the authors assume the mainlobe interference is the principal component of the array element signal. This study proposes the method based on the principal component analysis (PCA) and the extensive cancellation algorithm (ECA) to cancel the mainlobe interference in the echoes. The PCA is applied to extract the interference component from the array element signals, and the ECA is applied to cancel the interference with the extracted interference component as the reference. Finally, the simulation result proves the feasibility of the method proposed by this paper.
TDOA‐based adaptive observer trajectory optimisation algorithm for tracking in passive coherent location system
Authors: Jing Tong , Tian Wei , Huang Gaoming
Published: October 2019

In the passive coherent location system with fixed observers, the target tracking performance is limited by the inappropriate localisation geometry. This study proposes an adaptive observer trajectory optimisation (AOTO) algorithm in terms of minimising the geometric dilution of precision (GDOP) based on the time difference of arrival (TDOA) measurements gained from multiple emitters. The target states are estimated by the extended Kalman filter (EKF) algorithm. Simulation results demonstrate that the AOTO algorithm can effectively improve the tracking accuracy compared with the corresponding tracking approaches with fixed observers.
Micro‐Doppler feature extraction under passive radar based on orthogonal frequency division multiplexing communication signal
Authors: Qu Xiao‐yu , Li Kai‐ming , Zhang Qun , Liang Bi‐Shuai
Published: October 2019

Micro‐Doppler (m‐D) effect is a unique signature of radar targets with micro‐motion, which provides a new technique for target recognition. Passive radar based on communication signal has a great significance in detection and recognition for micro‐motion targets, low‐altitude surveillance and control, national air defences etc. In this study, based on orthogonal frequency division multiplexing communication signal, the echo modelling and analysis of rotating target are operated, and the expression of the target m‐D is deduced. Furthermore, the rotation frequency is extracted by sinusoidal frequency modulation Fourier‐Bessel series. The feasibility of the proposed method is proved by the simulation results. The method could offer a reference to feature extraction of micro‐motion targets under passive radar.
Deinterleaving method of complex staggered PRI radar signals based on EDW fusion
Authors: Tian Tian , Ni Jingjing , Jiang Yingying
Published: October 2019

Most of the existing pulse deinterleaving algorithms cannot deal well with complex staggered pulse repetition interval (PRI) radar signals which have >10 stagger levels. To solve this problem, a deinterleaving method based on emitter description word fusion is proposed here. The sub‐PRIs of a complex staggered PRI signal are detected by applying histogram statistics with overlapped PRI bins, then a data fusion is carried out to distinguish between complex staggered PRI signals and jittered PRI signals according to their characteristics in the set of PRI values. Furthermore, a general deinterleaving framework for PRI agility complex signals including jittered PRI signals, complex staggered PRI signals, and sliding PRI signals is also presented. Finally, experiments with collected real data demonstrate that the authors’ proposed method is very effective in deinterleaving of complex staggered PRI signals.
Investigating vertical motion of small insects in atmospheric boundary layer using millimetre‐wavelength radar and Doppler LIDAR
Authors: Wainwright Charlotte E. , Stepanian Phillip M. , Reynolds Don R. , Reynolds Andy M.
Published: October 2019

It is well known in the meteorological community that millimetre‐wavelength cloud radars contain considerable contamination from aerial biota, and much of this comprises small weakly flying insects. Several methods have been explored for removing insect contamination from cloud radar data yet using this data to study the behaviour of insects remains a relatively unexplored area. Here, the authors describe the use of a collocated Ka‐band cloud radar and Doppler LIDAR to study the vertical motion of small insects and investigate how this varies depending on the surrounding vertical air motion. We find that in the convective boundary layer, insects are largely concentrated in updrafts. During the daytime, small insects in downdrafts are found to descend at an average rate of 0.25 m s−1, yet insects caught in updrafts showed a descent response that was dependent upon the strength of the updraft in which they were embedded. Although the downward motion of the insects increased with increasing updraft strength, it was insufficient to overcome the rising motion in the updraft, i.e. in updrafts the insects ascend but at a slower speed than the surrounding air. We also report an ongoing efforts to extend this research to the nocturnal stable boundary layer.
Radar small/mini target detection technology in strong clutter environment
Authors: Wu Linyong , Mao Jin , Bai Weixiong
Published: October 2019

A method of radar small/mini target wavelet transform and principal component analysis in strong clutter environment is suggested. Focusing on the situation that the small/mini target in the strong clutter environment is swamped by clutter, traditional constant false‐alarm detection method limited by theory limit cannot effectively detect target, the transform domain, wavelet coefficient and principal component decomposition can realise the separation of radar small/mini target signal from the clutter signal, so as to achieve clutter suppression and small/mini target detection. The test shows the radar small/mini target detection based on wavelet transform is limited by wavelet function, decomposition layers and adaptive threshold; principal component decomposition can adapt to the signal of different radar systems, and types with good adaptability to algorithm can effectively suppress clutter and improve average signal‐to‐noise ratio by 7 dB.
Main‐lobe jamming cancellation for multi‐static radar by joint range‐Doppler processing
Authors: Jinli Meng , Ning Wang
Published: October 2019

It is well‐known that the noise jamming impedes the mission effectiveness of radar systems. It raises the level of the background and swamps out target returns. Techniques to suppress jamming and improve the performance of radar systems are continuously being developed. Here, a jammer being close to a target or even equivalent to it in direction, colloquially referred to as mainlobe jamming is considered. A mainlobe jamming cancellation technique based on multi‐static radar systems (MSRSs) is developed. In a MSRS, a jammer will produce different time delays and relative speeds to the diverse radar receivers located at separated positions. Here, the method to simultaneously estimate the shifts of time delay and Doppler frequency in the range‐Doppler plane (RDP) is proposed. Furthermore, the jamming cancellation is adaptively performed in the range‐Doppler domain. The simulation results show the validity of the proposed method.
Research on pulse compression radar angular glint modelling and suppression
Authors: Wang Chen , Feng Xiaobo , Zhang Wentao , Zhou Xiaoxiong
Published: October 2019

The target angular glint is the main factor restricting the tracking accuracy of radar at close range. There are few researches on angular glint of pulse compression radar. Here, the angular glint model of the large aerodynamic target under pulse compression is proposed. The field measured data verify the validity of the model. Second, a frequency‐diversity algorithm based on gating weighting is proposed to suppress angular glint. Simulation results show that its performance is better than the traditional frequency diversity algorithm. Third, the influence of total frequency hopping bandwidth and number of hopping on the frequency diversity algorithm is discussed. Finally, the algorithm proposed here has been applied with the existing experimental prototype. The outfield experiments show that the algorithm can suppress angle glint noise effectively.
Micro‐vibration distinguishment between humans and animals based on ensemble empirical mode decomposition using ultra‐wide band radar
Authors: Yin Yue , Yu Xiao , Lv Hao , Liu Miao , Qi Fugui , Wang Jianqi
Published: October 2019

Ultra‐wide band (UWB) bio‐radar attracts lots of researchers, due to its special advantages of non‐contact detection. It is widely used in multiple applications such as medical monitoring, rescue and anti‐terrorism missions nowadays. However, identifying the target after it was detected and located comes to be a more challenging task. The study aims to investigate the differences of the target characteristics between humans and animals based on ensemble empirical mode decomposition analysis and to test whether these differences can be distinguished. Finally, the authors proposed a new method to distinguish between humans and animals with 500 MHz UWB bio‐radar detection system by calculating the energy ratio of micro‐vibration signal in human breathing frequency band. Experimental results demonstrate that the energy ratio can be served as a useful parameter, which is promising to distinguish between humans and rabbits.
Efficient autofocus of small multi‐rotor UAV SAR by minimum entropy BP algorithm
Authors: Su Hao , Wei Shunjun , Zhang Xiaoling , Pu Limin , Yang Xiaoliang
Published: October 2019

Small multi‐rotor unmanned aerial vehicles (SMR‐UAVs) are a promising platform for low‐cost synthetic aperture radar (SAR) systems. However, SMR‐UAVs usually suffer from serious position errors due to their unstable motion and low actuary position sensors, and autofocus is an indispensable step for their high‐quality imaging. An efficient back‐projection autofocus method is proposed for SMR‐UAV SAR systems by the principle of minimum entropy. The position error estimation model via minimum entropy is derived. The conjugate‐gradient method is used to efficiently estimate the position errors. Moreover, to improve the computing efficiency, the strong scatterer areas are estimated as the input of entropy estimation. The effectiveness of the algorithm is demonstrated using both simulation and experimental data.
Passive radar polarisation filtering technology research
Authors: Yi Yucheng , Wan Xianrong , Yi Jianxin , Wang Ke
Published: October 2019

This study researches the potential benefits of clutter suppression in polarisation filtering technology. In the author's laboratory, the antenna of the experimental system has been designed, called dual‐polarised Yagi‐Uda antenna and the antenna can receive both horizontal and vertical polarisation simultaneously. The experimental results show that the method of improved polarisation filtering can suppress the clutter effectively, which is composed of direct‐path signal and multipath clutters.
Investigation on reason of range profile distortion of plasma sheath target
Authors: Cheng Zhi‐Wen , Zhao Xiao‐Tong
Published: October 2019

The range profile of the plasma sheath target is always found to be distorted when using the linear frequency modulation signal as the radar detection signal. As a result, the detection and tracking of the target became hard, or even failure. Here, three possible reasons of the range profile distortion is investigated in detail: (i) The broadening of the particles in the radial direction of the radar detection when the plasma sheath is produced; (ii) The scatterers in one range gate have different radial velocities that the range profile is dispersion due to the range‐Doppler coupling effect; (iii) The amplitude and frequency of the echo signal are modulated by the time‐varying plasma sheath. Here, the influence of the above three mechanisms on the range profile is simulated. In addition, for the accurate detection and tracking of these targets, the reason of the distortion should be distinguished. Therefore, several methods are proposed to distinguish the different mechanisms for the range profile distortion.
Adaptive detectors with enhanced selectivity capabilities in partially homogeneous environments
Authors: Wang Zeyu , Li Ming , Chen Hongmeng , Zuo Lei
Published: October 2019

This study deals with the problem of adaptive detection in the presence of mismatch signals in partially homogeneous environment. To enhance the selectivity of the detector, the authors add a fictitious signal under the null hypothesis. The fictitious signal is orthogonal to the nominal signal steering vector in the quasi‐whitened observation space. Two generalised likelihood ratio test‐based mismatch selective detectors are derived. Simulation results show that the one‐step mismatch selective detector coincides with the adaptive coherence estimator and the two‐step mismatch selective detector has a better mismatch rejection capability than the generalised adaptive matched filter.
Radar working‐state identification using the hidden Markov model
Authors: Zhang Wei , Gao Youbing , Zheng Kun
Published: October 2019

Using the statistical signal processing principle in the field of natural language processing, a radar state identification approach based on the hidden Markov model (HMM) is proposed. Since each radar state is modelled by three model parameters of a HMM, the radar state identification can be solved from the solution of the evaluation problem of a HMM. Simulation results show that the HMM‐based statistical identification method has tolerance to parameter error, which is suitable for the intelligent identification of the radar state in a complex environment.
Micro‐motion feature extraction of space targets based on sinusoidal frequency modulation Fourier transform
Authors: Hu Jian , Luo Ying , Zhang Qun , Liu Xiaowen , Qu Xiaoyu
Published: October 2019

The space target can be discriminated from other objects by the micro‐motion feature difference. The micro‐motion features of a space target with precession include the spinning period, the precession angle and the precession period etc. The main work of this study is to extract the target micro‐motion period from the echo by sinusoidal frequency modulation Fourier transform (SFMFT). The proposed method takes the advantages of the phase terms operation of the SFMFT. In the study, the micro‐Doppler effect induced by precession is analysed and then present the algorithm step by step. Meanwhile, the simulation is given to demonstrate the validity of the proposed method.