Online ISSN
1751-8792
Print ISSN
1751-8784
IET Radar, Sonar & Navigation
Volume 4, Issue 4, August 2010
Volumes & issues:
Volume 4, Issue 4
August 2010
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- Author(s): J. Wu ; T. Wang ; X. Meng ; Z. Bao
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 497 –506
- DOI: 10.1049/iet-rsn.2009.0121
- Type: Article
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p.
497
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(10)
Clutter suppression for airborne non-sidelooking radar is a challenging problem due to the range-dependent clutter. In this study, an algorithm combining elevation robust Capon beamforming (ERCB) and two-dimensional azimuth-Doppler space–time adaptive processing (STAP) is presented to realise clutter suppression for airborne non-sidelooking radar. The presented algorithm can place range-dependent nulls to eliminate the range-dependent clutter and the residual range-independent clutter can be suppressed by two-dimensional azimuth-Doppler STAP methods. Numerical examples are given to demonstrate the effectiveness of the presented algorithm. - Author(s): Y. Zhang ; Z. Ye ; X. Xu ; J. Cui
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 507 –519
- DOI: 10.1049/iet-rsn.2009.0104
- Type: Article
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p.
507
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(13)
In this study, a low complexity two-dimensional direction-of-arrival (2-D DOA) estimation method is proposed with uniform rectangular array (URA) when uncorrelated and coherent signals coexist. By using a new method of modified estimation of signal parameters via rotation invariance techniques (ESPRIT), the DOAs of uncorrelated signals are first estimated. Afterwards, the contributions of uncorrelated signals are eliminated, and then a new Toeplitz matrix without the information of uncorrelated signals is constructed. Using the product of the Toeplitz matrix and its conjugate transpose matrix, the remaining coherent signals can be resolved. With the two-step processing, the proposed method can resolve more signals with low computational complexity. Simulation results demonstrate the effectiveness and efficiency of the proposed method. The Cramer–Rao bound (CRB) for this signal scenario is also derived. - Author(s): B. Gallardo-Hernando ; F. Pérez-Martínez ; F. Aguado-Encabo
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 520 –527
- DOI: 10.1049/iet-rsn.2008.0212
- Type: Article
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520
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Wind farm installations that are near radar systems cause clutter returns that can affect the normal operation of the radar. Wind turbines provoke clutter reflectivity returns with unpredictable Doppler spreads that are not easily minimised. In this study, the authors focus on the mitigation of wind turbine clutter (WTC) for C-band weather radar. The proposed detection technique is applicable when using the spotlight operation mode during radar data gathering. This means that the dwell time must be long enough to observe certain statistics that allow for the detection of wind turbines. This specific operation mode can be used between normal radar scans. The detection technique can be applied before or after real rain data are added to WTC, with different results. Our mitigation technique uses the information from bins adjacent to WTC detections. The authors test this algorithm with real data from wind farms in rainy weather. The results are encouraging, because the absolute errors, both in reflectivity and in velocity measurements, are significantly reduced. - Author(s): C.-M. Yeh ; J. Xu ; Y.-N. Peng ; X.-G. Xia ; X.-T. Wang
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 528 –536
- DOI: 10.1049/iet-rsn.2009.0042
- Type: Article
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p.
528
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Rotational motion estimation is essential for inverse synthetic aperture radar (ISAR) imaging and understanding. For an object rotating with a constant acceleration, a closed-form solution is proposed to jointly estimate the initial rotating velocity (IRV) and the rotating acceleration (RA) by exploiting the pose difference of a triangle on two range-Doppler (RD) images. Then, the RA can be compensated with interpolation processing and an equivalent uniformly rotating object may be obtained. After that, the estimated IRV can be used to re-scale the RD image into the homogeneous range-cross range domain, or to provide more satisfactory imaging result via elaborated algorithms such as polar format algorithm or convolution back-projection algorithm. Finally, experimental results with both simulated and real airplane data are provided to demonstrate the effectiveness of the proposed method. - Author(s): A. De Maio ; S. De Nicola ; A. Farina ; S. Iommelli
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 537 –547
- DOI: 10.1049/iet-rsn.2009.0106
- Type: Article
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This study deals with adaptive detection of a signal with unknown complex amplitude and whose steering vector presents angle uncertainties. The background environment is assumed homogeneous and Gaussian with unknown covariance matrix. At the design stage, the authors devise a class of robust receivers accounting for the aforementioned uncertainty. To this end, the authors prove that the maximisation of the concentrated likelihood function over the phase parameter shares a hidden convexity property. Specifically, exploiting some recent results concerning trigonometric polynomials, the authors formulate the apparently non-convex maximisation over the phase as a semidefinite programming (SDP) convex optimisation problem. Then, the authors show that the receivers of the class (but for one) exhibit a bounded-constant false alarm rate (bounded-CFAR) behaviour and derive lower and upper bounds for both the false alarm and the detection performance. At the analysis stage, the authors assess the performance of the new receivers in comparison with some classic detectors available in open literature. - Author(s): L. Zhang ; M.-D. Xing ; C.-W. Qiu ; Z. Bao
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 548 –559
- DOI: 10.1049/iet-rsn.2008.0158
- Type: Article
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548
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In this study, the authors focus on the channel calibration for digital beam forming (DBF) synthetic aperture radar (SAR) imagery. Incorporated with DBF processing, multi-channel SAR is promising in high-resolution and wide-swath (HRWS) imaging. It coherently combines recorded multi-channel signals to overcome the spectrum ambiguity. However, the mismatch between channels and baseline errors phase should be compensated before the processing. In this study, the authors propose a novel calibration for DBF SAR imagery by making use of the orthognality between signal subspace and noise subspace. Based on that the imbalance is uncoupled in range and azimuth, the calibration has two steps: range calibration and azimuth calibration. The mismatch in range is estimated by an interpolation in time domain which is applicable in the presence of the Doppler ambiguity. The azimuth calibration is incorporated with the post-Doppler beam forming processing, which estimates the element error caused by baseline errors and channel imbalance. Real data are used to demonstrate the performance of Doppler ambiguity suppression after our calibration. The results confirm the validity of the approach. - Author(s): A. De Maio and E. Conte
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 560 –563
- DOI: 10.1049/iet-rsn.2009.0128
- Type: Article
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p.
560
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This study deals with the problem of detecting a radar target with unknown complex amplitude in the presence of clutter modelled as a spherically invariant random vector (SIRV). It is proved that, under a quite mild technical condition, the normalised matched filter (NMF) is the uniformly most powerful invariant (UMPI) detector in SIRV disturbance. The developed proof is based on the theory of total positive functions of order two. - Author(s): K.-T. Kim
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 564 –575
- DOI: 10.1049/iet-rsn.2007.0178
- Type: Article
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p.
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A new approach is presented to remove the motion effect of a maneuvering target in a high range resolution (HRR) profile based on stepped frequency waveform (SFW). The effects of target's motion in the SFW HRR profile consists of dispersion and translation shift of HRR profiles. The proposed approach exploits a subarray averaging concept in conjunction with the entropy cost function in order to find the translational velocity and acceleration of the target. By making use of the inherent properties of the proposed entropy-based cost function, the authors devise an efficient scheme for the two-dimensional (2-D) optimisation problem in the velocity and acceleration space, thereby improving the computational efficiency as well as the estimation accuracy significantly. Once the kinematic motion parameters are known, the unwanted dispersion of HRR profiles caused by the target's motion can be easily removed, providing focused HRR profiles with no dispersion. The proposed algorithm is especially useful for SFWs having low pulse repetition frequencies (PRFs) rather than those with high PRFs. The effectiveness of the algorithm is illustrated and analysed with simulated targets comprised of point scatters and a real aircraft radar cross-section data with artificial motion effects. - Author(s): S. Koteswara Rao ; K.S. Linga Murthy ; K. Raja Rajeswari
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 576 –585
- DOI: 10.1049/iet-rsn.2008.0109
- Type: Article
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p.
576
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Underwater manoeuvring target rarely tracked using bearings-only measurements available from Hull mounted array (HA) without a proper manoeuvre by the observer. This problem is solved by administering data fusion techniques on bearings available from towed array and HA. Song and Speyer's and Galkowski and Islam's modified gain bearings only extended Kalman filter is exploited for estimation of target motion parameters. Online pre-processing is carried out to reduce the amplitude of the noise, compute the estimated bearings if the bearing measurement is not available and to find out variance of the noisy measurement which is used in Kalman filter. The spurious measurements are made invalid. The performance evaluation of the algorithms is done in Monte-Carlo simulation and results obtained for two typical geometries are presented. - Author(s): J.M. Muñoz-Ferreras ; F. Pérez-Martínez ; M. Datcu
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 586 –594
- DOI: 10.1049/iet-rsn.2009.0027
- Type: Article
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p.
586
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In order to obtain focused inverse synthetic aperture radar (ISAR) images, an accurate translational motion compensation is required. The phase adjustment step corresponds to fine compensation and must be properly designed. The authors introduce the Rényi entropy for autofocusing ISAR images. The Rényi entropy of order α is a generalisation of the standard Shannon entropy. When α tends to be the unity, the Rényi entropy tends to be the Shannon entropy. Here, we demonstrate that minimising the Rényi entropy for α=2 is equivalent to maximising the contrast for ISAR autofocusing. Furthermore, it is also shown that maximising the peak value is equivalent to minimising the Rényi entropy for α tending to infinity. On the other hand, the authors propose to minimise the Rényi entropy with α=0.5 to reconstruct an accurate ISAR image. Simulated data have been used to verify that, in terms of mean squared error, the proposed method with α=0.5 outperforms other autofocusing algorithms such as the method based on contrast maximisation or the one based on the minimisation of the standard Shannon entropy. The method has also been applied to real data. - Author(s): J. Su ; M. Xing ; G. Wang ; Z. Bao
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 595 –603
- DOI: 10.1049/iet-rsn.2008.0160
- Type: Article
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High-speed multi-target detection is a challenging problem in radar applications. Typically, targets with high speed go through several range cells in the observation period, which makes it more difficult to obtain each target's power coherently accumulated for target detection. In this study, novel multi-target detection with a narrowband radar system is proposed. In order to remove range migration and obtain coherent integration of the target energy, the Keystone transform is applied to the moving targets. However, because of the high target velocity and the low radar pulse repetition frequency phase ambiguity will occur, so the range migration will not be corrected properly. Then the phase ambiguity function of the kth target is compensated, and the envelope of the kth target concentrates in a certain range cell. Following by frequency modulation rate search a quadratic phase term is compensated, and the signal energy is finally coherently accumulated by FT analysis. The target is detected if the ratio of peak value to noise is higher than a predetermined threshold. For target detection in low signal-to-noise ratio (SNR), the Clean technique is applied. The proposed algorithm is verified by simulation and raw radar data results. - Author(s): C.J. Hung and C.H. Chen
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 604 –610
- DOI: 10.1049/iet-rsn.2009.0177
- Type: Article
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This study presents a new direction-of-arrival (DOA) estimation technique with application to the uniform linear sensor array for rapidly varying signals in the uncorrelated or coherent case. Unlike the conventional subspace-based algorithms, it need not form the covariance matrix using a block of the array data, a complicated computational burden and a prior knowledge of the number of incoming signals. This approach is based on the technologies of the shrinking signal subspace and the noise pseudo-eigenvector. In contrast with Kim's method, our purposed algorithm can improve its performance of resolution capabilities but requires less computational complexity. Computer simulation results that demonstrate the resolution performance of the proposed algorithm are included. Since the algorithm is simple and can maintain resolution capabilities as compared to Kim's method, it may be used on its own to provide a wider application prospect in real-time DOA estimation or be used as good initialisation for more complex and more high-resolution DOA algorithms. - Author(s): E. Yang ; R. Adve ; J. Chun ; J. Chun
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 611 –625
- DOI: 10.1049/iet-rsn.2007.0173
- Type: Article
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p.
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(15)
The need to deal with non-homogeneous clutter has driven much of the recent research in space–time adaptive processing (STAP). An extension of the low-complexity, sigma-delta (ΣΔ) algorithm incorporating the direct data domain (D3) processing is presented. The new algorithm is practical and improves target detection in non-homogeneous clutter environments. The algorithm employs a hybrid approach, combining D3 processing with the more traditional statistical approach, thereby obtaining advantages of both. First, a modified D3 algorithm, which maximises signal-to-interference-plus-noise ratio (SINR), is presented. Then this D3 algorithm is used as an adaptive transformer to create sum (Σ) and difference (Δ) beams. The residual interference after the D3 processing is further cancelled by ΣΔ STAP. The proposed hybrid algorithm using D3-ΣΔ STAP is tested in non-homogeneous clutter modelled using spherically invariant random variables (SIRV) and artificially injected discrete interferers. Performance of the proposed methods is compared with those of traditional statistical approaches, illustrating significant benefits of hybrid processing in non-homogeneous scenarios. - Author(s): B. Rao ; Y.-L. Zhao ; S.-P. Xiao ; X.-S. Wang
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 626 –638
- DOI: 10.1049/iet-rsn.2009.0033
- Type: Article
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Range deception is a common electronic countermeasure technique used for ballistic missile penetration. The well-designed decoys of range deception can even form stable tracks. Discrimination of these decoys is difficult and one potential way is at radar data processing level by using motion features. This study presents a novel method, called acceleration matched discrimination algorithm, which fully utilises the fact that the accelerations of exo-atmospheric active decoys are essentially different from that of physical targets (e.g. warhead), that can discriminate these decoys at the radar data processing level. First, the acceleration model of active decoys is explicitly derived. Secondly, the acceleration matched coefficient (AMC) is defined based on the filtered acceleration and theoretical acceleration. By employing the extended Kalman filter, the instantaneous variance of AMC is also derived. Finally, the discrimination algorithm is designed based on a batch-processing weighted least squares estimate and its estimated variance. Theoretical analysis and simulations indicate that the discrimination method is valid and feasible. Furthermore, the discrimination performance analysis due to the influence of radar position, radar measurement error and data rate are also covered. - Author(s): R.O. Lane
- Source: IET Radar, Sonar & Navigation, Volume 4, Issue 4, p. 639 –648
- DOI: 10.1049/iet-rsn.2009.0094
- Type: Article
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p.
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Super-resolution of signals and images can improve the automatic detection and recognition of objects of interest. However, the uncertainty associated with this process is not often taken into consideration. This is important because the processing of noisy signals can result in spurious estimates of the scene content. This study reviews a variety of super-resolution techniques and presents two non-parametric Bayesian super-resolution algorithms that not only take uncertainty into account, but also retain knowledge about the output uncertainty in the form of a full probability distribution. One of the two Bayesian techniques is based on an analytical calculation re-interpreted as super-resolution, and the other is a novel numerical algorithm. Although the algorithms are presented as stand-alone techniques for image analysis, such Bayesian super-resolution algorithms can increase automatic target recognition performance over standard super-resolution.
Clutter suppression for airborne non-sidelooking radar using ERCB-STAP algorithm
Estimation of two-dimensional direction-of-arrival for uncorrelated and coherent signals with low complexity
Detection and mitigation of wind turbine clutter in C-band meteorological radar
Rotational motion estimation for ISAR via triangle pose difference on two range-Doppler images
Adaptive detection of a signal with angle uncertainty
Adaptive two-step calibration for high-resolution and wide-swath SAR imaging
Uniformly most powerful invariant detection in spherically invariant random vector distributed clutter
Focusing of high range resolution profiles of moving targets using stepped frequency waveforms
Data fusion for underwater target tracking
Generalisation of inverse synthetic aperture radar autofocusing methods based on the minimisation of the Rényi entropy
High-speed multi-target detection with narrowband radar
New algorithm for fast direction-of-arrival estimation using the shrinking signal subspace and the noise pseudo-eigenvector
Hybrid direct data domain sigma-delta space–time adaptive processing algorithm in non-homogeneous clutter
Discrimination of exo-atmospheric active decoys using acceleration information
Non-parametric Bayesian super-resolution
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