Online ISSN
1751-8792
Print ISSN
1751-8784
IET Radar, Sonar & Navigation
Volume 1, Issue 1, February 2007
Volumes & issues:
Volume 1, Issue 1
February 2007
-
- Author(s): Z.L. Liu ; Y.C. Guo ; G.Y. Zhang ; J.F. Xu
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 1 –7
- DOI: 10.1049/iet-rsn:20060026
- Type: Article
- + Show details - Hide details
-
p.
1
–7
(7)
When the airborne fire control radar operates with the high pulse-repetition frequency (PRF) in the frequency-modulated ranging mode, the range measurement is ambiguous. Here, the problem of target range estimation and ambiguity resolving is converted to the problem of static multiple models estimation and decision. Frequency and pseudo-range measurements are used to update each model of the target with the probabilistic data association and tracking filter. The method to select the PRF used to detect the target is also suggested according to the state estimates of the survived models. Simulation results demonstrate the improved accuracy and convergence when compared with the conventional methods. - Author(s): D.G. Khairnar ; S.N. Merchant ; U.B. Desai
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 8 –17
- DOI: 10.1049/iet-rsn:20050023
- Type: Article
- + Show details - Hide details
-
p.
8
–17
(10)
A new approach using a radial basis function network (RBFN) for pulse compression is proposed. In the study, networks using 13-element Barker code, 35-element Barker code and 21-bit optimal sequences have been implemented. In training these networks, the RBFN-based learning algorithm was used. Simulation results show that RBFN approach has significant improvement in error convergence speed (very low training error), superior signal-to-sidelobe ratios, good noise rejection performance, improved misalignment performance, good range resolution ability and improved Doppler shift performance compared to other neural network approaches such as back-propagation, extended Kalman filter and autocorrelation function based learning algorithms. The proposed neural network approach provides a robust mean for pulse radar tracking. - Author(s): L. Du ; H. Liu ; Z. Bao ; J. Zhang
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 18 –26
- DOI: 10.1049/iet-rsn:20050119
- Type: Article
- + Show details - Hide details
-
p.
18
–26
(9)
Radar high-resolution range profile (HRRP) has received intensive attention from the radar automatic target recognition (RATR) community. Usually, since the initial phase of a complex HRRP is strongly sensitive to target position variation, only the amplitude information in complex HRRPs is used for RATR, whereas the phase information is discarded. However, the remaining phase information except for initial phases in complex HRRPs may also contain valuable target discriminant information. RATR using complex HRRPs is discussed. The complex HRRPs' feature subspace within each target-aspect sector is extracted via principal component analysis as the corresponding template during the training phase; while in the test phase we decide that a test sample belongs to the feature subspace which has the test sample's minimum reconstruction error approximation. It is shown that the whole process is independent of the initial phases, but exploits the remaining phase information in complex HRRPs. Furthermore, to make the proposed recognition method more practical, a fast time-shift compensation algorithm is proposed. In the recognition experiments based on measured data, the proposed recognition method using complex HRRPs achieves better recognition results than that using only the amplitude vectors of the complex HRRPs. - Author(s): M. Tria ; J.P. Ovarlez ; L. Vignaud ; J.C. Castelli ; M. Benidir
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 27 –37
- DOI: 10.1049/iet-rsn:20050124
- Type: Article
- + Show details - Hide details
-
p.
27
–37
(11)
New technique based on continuous wavelet transform (CWT) for classifying objects in synthetic aperture radar (SAR) imaging is presented. The CWT allows to analyse two-dimensional SAR images to highlight the frequency and angular behaviour of the scatterers ref. 10, 11. This technique allows to build a SAR hyperimage, that is, a four-dimensional data cube which represents for each spatial location (x, y) of the scatterer in the image, its frequency and angular energy behaviour. When analysing different targets, objects or areas in SAR images, it has been recently observed that some scatterers belonging to a same class of objects could have similar frequency and angular energy responses. The previous observations have motivated the determination to exploit these energy responses to discriminate these objects. This discrimination is performed by frequency and angular correlations between the response of a particular scatterer (measured) and those of all the scatterers in the SAR image. Some examples of discrimination from real SAR data are presented and show an interest of the method for target classification and recognition for SAR imaging. - Author(s): M. McDonald and B. Bhashyam
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 38 –49
- DOI: 10.1049/iet-rsn:20050156
- Type: Article
- + Show details - Hide details
-
p.
38
–49
(12)
A de-emphasis weighting approach is used to suppress the effect of outliers in background samples during the formation of a sample covariance matrix. The approach is relevant to a broad range of adaptive filtering techniques. Results from processing simulated and real coherent radar data using de-emphasis weighting are compared with results using no outlier suppression and censored sample matrix inversion pruning methods. De-emphasis techniques are shown to produce the most robust detection performance when outliers are present and are also shown to have minimal performance impact when clutter is homogeneous, that is no outliers present. - Author(s): J.P. Bustos ; F. Donoso ; A. Guesalaga ; M. Torres
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 50 –58
- DOI: 10.1049/iet-rsn:20060025
- Type: Article
- + Show details - Hide details
-
p.
50
–58
(9)
A novel technique to obtain position, velocity and radar biases estimates of a ship is described by matching ship-borne radar images to geo-referenced satellite images. The matching is performed through the minimisation of the averaged partial Hausdorff distances between data points in each image. The minimisation rapidly yields robust geographical latitude and longitude position measurements, as well as ship heading and radar biases. The accuracy of the measurements is improved by feeding them into a Kalman filter that also allows estimates of the ship's velocity to be obtained. The method provides an alternative effective position sensor for GPS denied environments, which may also be employed for automatic radar calibration of bearing and range biases or for indoor autonomous mobile robot navigation. - Author(s): F. Zhou ; R. Wu ; M. Xing ; Z. Bao
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 59 –66
- DOI: 10.1049/iet-rsn:20060040
- Type: Article
- + Show details - Hide details
-
p.
59
–66
(8)
In recent years, ground moving target imaging in synthetic aperture radar (SAR) has attracted the attention of many researchers all over the world. A novel approach is proposed for the ground moving target imaging and motion parameter estimation using single channel SAR. First, a second-order generalised keystone formatting method is used to compensate for the range curvature. Secondly, the estimated slope of the target echo's envelope is used for the range walk compensation. Thirdly, Doppler parameters of moving targets obtained via spectral analysis are used for the imaging and positioning of ground moving targets. Finally, motion parameters of moving targets can be estimated on the basis of the relationship between Doppler and motion parameters. Both numerical and experimental results are provided to demonstrate the performance of the proposed approach. - Author(s): N.M. Harwood ; W.N. Dawber ; D.J. King ; V.A. Klückers ; G.E. James
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 67 –73
- DOI: 10.1049/iet-rsn:20060042
- Type: Article
- + Show details - Hide details
-
p.
67
–73
(7)
An extension to the traditional two-element array crosseye interferometric electronic jamming technique is investigated. Simulations are performed to obtain excitations for multiple-emitter linear arrays that produce distorted wavefronts over desired regions of space. This results in a greater number of degrees-of-freedom and a better ability to control the desired field pattern. The crosseye effect can be achieved over wider sectors, but only by increasing array power. The technique is extended to two-dimensional arrays and is applicable to multi-function radar antennas. Experimental measurements performed on a four-emitter array demonstrate the feasibility of the technique. Good agreement with predictions is shown. - Author(s): B. Ristic and M. Morelande
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 74 –76
- DOI: 10.1049/iet-rsn:20060067
- Type: Article
- + Show details - Hide details
-
p.
74
–76
(3)
In a recent paper, Ristic et al., 2004, proposed a simple and exact derivation of the theoretical Cramér–Rao lower bound (CRLB) for tracking multiple targets using intensity maps as measurements. Although the formulation and the theoretical derivations presented in their work are indeed correct, the analysis of the proposed bound and the conclusions that follow are wrong. Here, a correct analysis is presented with the key observation that [as opposed to the claim made in the work of Ristic et al. (2004)], the proposed CRLB reflects the interaction between the targets, even if their motion is independent. The multi-target CRLB is also compared with the error performance of a multi-target state maximum likelihood estimator; a remarkable agreement is observed for high signal-to-noise ratio. - Author(s): H.-S. Shin and J.-T. Lim
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 77 –82
- DOI: 10.1049/iet-rsn:20060080
- Type: Article
- + Show details - Hide details
-
p.
77
–82
(6)
Since the reference signal based on the fixed reference range is used in the range migration algorithm (RMA), the RMA is not available to process an airborne squint-mode spotlight synthetic aperture radar (SAR) data. Thus, the modified reference signal to transform a squint-mode data to a broadside-mode data is introduced on the basis of the coordinate transformation and the extended Taylor approximation. Then, using the principle of the stationary phase, the presented formulation is analysed. Moreover, to compensate curvature errors, the proposed method is extended on the basis of the subarea technique. Finally, the effectiveness of the proposed method is demonstrated by some numerical simulations via a pulsed spotlight SAR simulator. - Author(s): E. Coiras ; P.-Y. Mignotte ; Y. Petillot ; J. Bell ; K. Lebart
- Source: IET Radar, Sonar & Navigation, Volume 1, Issue 1, p. 83 –90
- DOI: 10.1049/iet-rsn:20060098
- Type: Article
- + Show details - Hide details
-
p.
83
–90
(8)
A proof of concept for a model-less target detection and classification system for side-scan imagery is presented. The system is based on a supervised approach that uses augmented reality (AR) images for training computer added detection and classification (CAD/CAC) algorithms, which are then deployed on real data. The algorithms are able to generalise and detect real targets when trained on AR ones, with performances comparable with the state-of-the-art in CAD/CAC. To illustrate the approach, the focus is on one specific algorithm, which uses Bayesian decision and the novel, purpose-designed central filter feature extractors. Depending on how the training database is partitioned, the algorithm can be used either for detection or classification. Performance figures for these two modes of operation are presented, both for synthetic and real targets. Typical results show a detection rate of more that 95% and a false alarm rate of less than 5%. The proposed supervised approach can be directly applied to train and evaluate other learning algorithms and data representations. In fact, a most important aspect is that it enables the use of a wealth of legacy pattern recognition algorithms for the sonar CAD/CAC applications of target detection and target classification.
Multiple models track algorithm for radar with high pulse-repetition frequency in frequency-modulated ranging mode
Radial basis function neural network for pulse radar detection
Radar automatic target recognition using complex high-resolution range profiles
Discriminating real objects in radar imaging by exploiting the squared modulus of the continuous wavelet transform
Outlier suppression in adaptive filtering through de-emphasis weighting
Matching radar and satellite images for ship trajectory estimation using the Hausdorff distance
Approach for single channel SAR ground moving target imaging and motion parameter estimation
Multiple-element crosseye
Comments on ‘Cramér–Rao lower bound for tracking multiple targets’
Range migration algorithm for airborne squint mode spotlight SAR imaging
Supervised target detection and classification by training on augmented reality data
Most viewed content for this Journal
Article
content/journals/iet-rsn
Journal
5
Most cited content for this Journal
-
Target recognition in synthetic aperture radar images via non-negative matrix factorisation
- Author(s): Zongyong Cui ; Zongjie Cao ; Jianyu Yang ; Jilan Feng ; Hongliang Ren
- Type: Article
-
Overview of frequency diverse array in radar and navigation applications
- Author(s): Wen-Qin Wang
- Type: Article
-
Phase-modulation based dual-function radar-communications
- Author(s): Aboulnasr Hassanien ; Moeness G. Amin ; Yimin D. Zhang ; Fauzia Ahmad
- Type: Article
-
Review of micro-Doppler signatures
- Author(s): Dave Tahmoush
- Type: Article
-
Compressive sensing-based inverse synthetic radar imaging imaging from incomplete data
- Author(s): Sonia Tomei ; Alessio Bacci ; Elisa Giusti ; Marco Martorella ; Fabrizio Berizzi
- Type: Article
