IET Radar, Sonar & Navigation
Volume 12, Issue 4, April 2018
Volumes & issues:
Volume 12, Issue 4
April 2018
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- Author(s): Zukun Lu ; Huaming Chen ; Feiqiang Chen ; Junwei Nie ; Gang Ou
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 383 –389
- DOI: 10.1049/iet-rsn.2017.0416
- Type: Article
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p.
383
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A blind adaptive channel mismatch equalisation method for global navigation satellite system (GNSS) antenna arrays is proposed. The anti-jamming performance of the antenna arrays is limited by the channel mismatch that is a relative characteristic of each radio frequency channel but not an absolute non-ideal characteristic. To pre-process the received data in the frequency domain, the least mean square (LMS) algorithm is used. The reference signal in LMS is the received data in the reference element. The purpose of pre-processing is to make the received data in the other elements approach the reference signal, which, in essence, is to equalise the mismatched channel. Without any auxiliary sensors and calibration source, this method can estimate the channel characteristics relative to the reference elements. Simulations and experimental results show that the proposed method is significant in improving the anti-jamming performance.
- Author(s): Qi-Yong Liu ; Qun Zhang ; Ying Luo ; Kai-Ming Li ; Li Sun
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 390 –397
- DOI: 10.1049/iet-rsn.2017.0319
- Type: Article
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p.
390
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In traditional compressed sensing theory, the authors have to adopt a discretisation procedure to reduce the continuous parameter space to a finite set of grid points. The discretisation procedure will cause the off-grid effect, which result in the reconstruction result unstable. To solve this problem, an alternating iteration algorithm is proposed which is built on the greedy-like algorithms. Firstly, a multilayer first-order approximation model is proposed to approximate the true observation model in the off-grid model. Then, an alternating iteration algorithm is proposed to estimate the sparse signal and mismatch factor. Moreover, the computational complexities of the proposed algorithm with different greedy algorithms are discussed. Finally, simulations demonstrate the good performance of the proposed algorithm. Meanwhile, the performance of the proposed method will not be influenced by the correlation of dictionary matrix and mismatch matrix.
- Author(s): Xuebing Xiao ; Fucheng Guo ; Daowang Feng
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 398 –406
- DOI: 10.1049/iet-rsn.2017.0368
- Type: Article
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p.
398
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A joint time delay and Doppler shift estimation of unknown wideband signals is studied in the sense that the variation of time delay over time and the migration of Doppler shift over signal frequency cannot be neglected. By partitioning the received signals into short time segments, a novel wideband signal model is proposed. Based on this model, the maximum likelihood estimate (MLE) of the time delay at the starting point of observation and the Doppler shift at the signal carrier frequency is derived. With well compensation of the migrations of these parameters, the MLE derived could achieve higher estimation accuracy. To lower the computational complexity, a fast estimation algorithm based on the Keystone transform is also presented. After correcting the migrations through the Keystone transform, successive one-dimensional Fourier transform, instead of two-dimensional grids search, is used to achieve coherent processing of the received signals. The Cramer–Rao lower bound analysis for wideband cases is presented and the computational complexity of the proposed algorithms is analysed. Simulation results demonstrate the superiority of the proposed methods for wideband cases.
- Author(s): Mengnan Wang ; Zhuang Wang ; Zhu Cheng ; Jing Chen
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 407 –416
- DOI: 10.1049/iet-rsn.2017.0435
- Type: Article
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p.
407
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The troposcatter over-the-horizon (OTH) passive radar plays an important role in the beyond-line-of-sight surveillance, for its high propagation reliability and low probability of interception. However, it has two major limitations, namely, large propagation losses and multipath scattering fading. Since the captured signals are non-stationary with low signal-to-noise ratio, high antenna gain is indispensable, which results in narrow beamwidth. To deal with the contradiction between narrow beamwidth and real-time wide spatial coverage, array receiving is promising. Then, the primary problem is the array signal detection under troposcatter fading correlations. Based on recent troposcatter fading model, this study addresses this passive detection problem in three cases: (i) the spatial–temporal correlation is known, and a Neyman–Pearson detector is proposed as benchmark; (ii) uncertain statistics exist in the spatial–temporal correlation, and a generalised likelihood ratio test is adopted to overcome this uncertainty; (iii) the fading correlation is totally unknown, and a spatial–temporal weighted covariance-based detector is proposed. The performances of the proposed detectors are verified by Monte-Carlo simulations and experiments in a linear array, which is instructive for this kind of passive radar design in practical. Comparisons with existing detectors and the benchmark confirm the feasibility and effectiveness for troposcatter OTH passive radar.
- Author(s): Long Li ; Zheng Liu ; Tao Li
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 417 –425
- DOI: 10.1049/iet-rsn.2017.0391
- Type: Article
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p.
417
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For radar automatic target recognition, the features should be extracted with sufficient target information, high discrimination, noise robustness and low feature vector dimension. In this study, a novel method for HRRP feature extraction is proposed, named as multiple kernel projection subspace fusion (MKPSF) method. For MKPSF, the statistical characteristics of both strong and weak scattering range cells are effectively exploited with an improved projection subspace extraction method. Therefore, the integrity of target information and the noise robustness can be ensured for HRRP recognition. In addition, a novel criterion function is constructed based on feature fusion and Fisher criterion theories. In this criterion function, the within-class correlation and between-class discrimination are maximised to guarantee high discrimination for feature vectors. Besides, the redundancy and dimensionality of the feature vectors are reduced by a fusion operation within the criterion function. This facilitates the reduction of the computational complexity in the practical radar target recognition system. Experimental results with measured datasets validate the efficiency of the proposed method.
- Author(s): Jaegyu Jang ; Seungwoo Seo ; Woo-Guen Ahn ; Jangyong Lee ; Junpyo Park
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 426 –432
- DOI: 10.1049/iet-rsn.2017.0142
- Type: Article
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p.
426
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This study describes the theoretical performance of a successive interference cancellation (IC) technique as an electronic counter countermeasure and verifies its feasibility through experiments. In a radio navigation system using direct sequence/code division multiple access, strong pseudorandom signals can be used as interference sources for unauthorised users when regional radio navigation needs to be denied in a specific area, while authorised users can use both the strong signal and the global navigation satellite system (GNSS) ranging signal for navigation through the IC method. To determine the feasibility of this selective jamming concept, this study investigated its theoretical performance and compared the results with experimental ones. The experimental results show that a maximum jamming-to-signal ratio performance of 57 dB or higher can be achieved, which is similar to the theoretical estimation.
- Author(s): Tian Zhou ; Dongdong Peng ; Chao Xu ; Wanyuan Zhang ; Jiajun Shen
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 433 –441
- DOI: 10.1049/iet-rsn.2017.0239
- Type: Article
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p.
433
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Terrain aided navigation (TAN) is a promising approach to bound accumulated errors inherent to inertial navigation system by comparing terrain measurement with a reference map. Due to the non-linear nature of terrain, particle filters (PFs) are extensively studied for TAN because of its strong capability of dealing with non-linear problems. So far, most existing PFs for TAN manually select a fixed number of sampling particles during the entire filtering process. However, it can be highly inefficient, since the probability distribution of the state often varies drastically over time. To improve the efficiency, the Fox's adaptive PF based on Kullback–Leibler distance (KLD) is introduced for TAN, referred to as the normal KLD-PF here. In the normal KLD-PF, the number of sampling particles is adjusted online by KLD-sampling according to the size of state space. However, the normal KLD-PF has a fixed bin size, which easily causes the number of particles to surge at the early filtering stage. Thus, an improved KLD-PF with a variable bin size is proposed through limiting the total number of particles below certain value. Using a multi-beam sonar, simulation experiments with real underwater reference map demonstrate the efficiency of the proposed method.
- Author(s): Pengbin Guo ; Jian Sun ; Ju Xue
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 442 –448
- DOI: 10.1049/iet-rsn.2017.0571
- Type: Article
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p.
442
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Pulsar navigation has gradually attracted increased attention because of its unique advantages in the study of high-attitude missions and deep space exploration. Low navigation accuracy, due to the long integration period, is one of the main problems with X-ray pulsar navigation. In this study, a new observation strategy for pulsar navigation that could greatly increase observations compared with the traditional synchronous observation model has been proposed. Due to the uncertainty of the measured angles of the pulsar navigation model, a robust Kalman filter was designed based on the new observation model, and mathematical simulation results showed that the proposed method had improved navigation accuracy.
- Author(s): Mei Liu ; Zhigui Wang ; Pengfei Wang
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 449 –457
- DOI: 10.1049/iet-rsn.2017.0450
- Type: Article
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Multi-dimensional reconstruction of ground is one of the most important applications of differential synthetic aperture radar tomography (D-TomoSAR) system. The ground deformation model is considered to be linear in classical D-TomoSAR system model. However, the real deformation in practice is deviated from the linear model, and the deformation parameters cannot be estimated accurately by spectral estimation. Here, a polynomial deformation model is proposed to approach the real motion of the ground. Since the deformation history appears as a phase term in the model of D-TomoSAR system, the corresponding model could be extended to a two-dimensional (2D) polynomial phase signal (PPS) by introducing the polynomial deformation model. In addition, an effective method combining the 2D product high-order ambiguity function with 2D-RELAXation (RELAX) algorithm is provided to estimate the coefficients of this 2D-PPS. Theoretical analyses and experimental results show that the ground elevation, linear and non-linear motions can be both estimated accurately, and it is possible to separate scatterers distributed along the slant height within a resolution cell with the proposed method.
- Author(s): Jun Zhang ; Guisheng Liao ; Jingwei Xu ; Yuhong Zhang ; Shengqi Zhu
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 458 –465
- DOI: 10.1049/iet-rsn.2017.0382
- Type: Article
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p.
458
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Bistatic circular synthetic aperture radar (BCSAR) can realise super-resolution imaging of the complex scenario and eliminate sheltering of the straight line wave propagation. However, BCSAR encounters the ring effect and high sidelobe problem due to the discontinuity of Fourier sampling space induced by the limited signal bandwidth, which causes severe performance degradation in the final image. In this study, the Fourier sampling theory is used as a new analytical tool to study the high sidelobe problem existed in BCSAR, and a new BCSAR scheme, referred to as geometric diversity-based BCSAR (GD-BCSAR) is introduced, then its sampled Fourier area (SFA) and image resolution are further analysed. GD-BCSAR can overcome the limit of signal bandwidth and obtain a larger SFA. Therefore, the discontinuity of Fourier sampling space becomes weaker, which could reduce the ring effect and the sidelobe level significantly. The simulated results are presented to validate the effectiveness of the GD-BCSAR scheme and corresponding performance analysis.
- Author(s): Suleyman Ayazgok ; Cihangir Erdem ; Mustafa Talha Ozturk ; Adnan Orduyilmaz ; Mahmut Serin
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 466 –474
- DOI: 10.1049/iet-rsn.2017.0354
- Type: Article
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p.
466
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Cognitive electronic warfare (EW) is the key feature for next-generation EW systems. The deinterleaving and classification of received radar pulses and selection of the proper electronic attack technique are the common issues for non-preprogrammed cognitive jamming systems. Antenna scan type (AST) is a dominant parameter to discriminate and solve the ambiguities for the classification of the radar threats. In the literature, there are solutions for the classification of conical, helical, raster, and bidirectional scan types. In this study, spiral and electronic scan types are introduced in the AST analysis algorithm. Moreover, a new method based on correlation is proposed to determine the main beam signal. The proposed method gives better performance than amplitude thresholding-based algorithms for not only newly added but also other scan types. Also, main beam flatness ratio is proposed as a new feature to separate electronic scan types from the other scan types. Intensive simulations are executed to evaluate the performance of the proposed new method and feature. The classification of the conical, spiral, helical, circular, raster, and sector scan types at ∼15 dB signal-to-noise ratio (SNR) is completed with 98% success. For electronic scan types, at least 94% classification accuracy is observed for SNR values above 20 dB.
- Author(s): Rakesh Sharma and Rajib Kumar Panigrahi
- Source: IET Radar, Sonar & Navigation, Volume 12, Issue 4, p. 475 –483
- DOI: 10.1049/iet-rsn.2017.0313
- Type: Article
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p.
475
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In this study, a speckle filtering technique is proposed for coherent compact polarimetric synthetic aperture radar (PolSAR) data based on the statistics of Stokes parameters. The data processing and analysis of coherent compact PolSAR configurations usually start with Stokes vector representation of the data. In this study, the Stokes parameter statistics is discussed and validated, and a modified form of the state-of-the-art Lee sigma filter for compact PolSAR data is presented. Also, a novel algorithm for evaluation of sigma ranges as a function of the degree of polarisation and mean intensities is proposed. An approach based on the statistics of Stokes parameter for the distinction of homogeneous and heterogeneous areas is also presented in this study. The proposed technique is effective in speckle reduction, preservation of fine details, strong targets and scattering information. The decomposition with the proposed filter as a pre-processing step improves the land cover classification accuracy. The computational efficiency of the proposed filter is comparable to Lee sigma filter and hence the proposed filter is equally suitable for voluminous high resolution datasets. The results obtained from the developed speckle filter are validated for hybrid-PolSAR RISAT-1 data, hybrid-PolSAR data synthesised from RADARSAT-2 data and simulated PolSAR data by Monte Carlo simulation.
Blind adaptive channel mismatch equalisation method for GNSS antenna arrays
Fast algorithm for sparse signal reconstruction based on off-grid model
Low-complexity methods for joint delay and Doppler estimation of unknown wideband signals
Target detection for a kind of troposcatter over-the-horizon passive radar based on channel fading information
Radar high-resolution range profile feature extraction method based on multiple kernel projection subspace fusion
Performance analysis of an interference cancellation technique for radio navigation
Adaptive particle filter based on Kullback–Leibler distance for underwater terrain aided navigation with multi-beam sonar
X-ray pulsar navigation using multiple detectors based on a new observation strategy
Extension of D-TomoSAR for multi-dimensional reconstruction based on polynomial phase signal
Study on performance of bistatic circular synthetic aperture radar imaging using geometric diversity
Automatic antenna scan type classification for next-generation electronic warfare receivers
Stokes based sigma filter for despeckling of compact PolSAR data
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