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Radar, Sonar & Navigation, IET

Issue 8 • Date Oct. 2011

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Displaying Results 1 - 12 of 12
  • Direction finding in frequency-modulated-based passive bistatic radar with a four-element adcock antenna array

    Publication Year: 2011 , Page(s): 807 - 813
    Cited by:  Papers (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (502 KB)  

    The Adcock antenna array is widely used in electronic warfare for direction finding of emitter sources. However, in frequency modulated (FM)-based passive bistatic radar (PBR) the traditional Adcock antenna-based direction finding methods cannot work well because weak target echoes are embedded in the background of strong direct signals, multipath and clutter echoes. A method using a four-element Adcock antenna array is developed for horizontal plane 360° target direction measurements for FM-based PBR. By using numerical simulations, the performance of the proposed method is studied for both single and multiple targets, and finally its effectiveness is demonstrated for real data. View full abstract»

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  • Ground vehicle navigation in harsh urban conditions by integrating inertial navigation system, global positioning system, odometer and vision data

    Publication Year: 2011 , Page(s): 814 - 823
    Cited by:  Papers (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (938 KB)  

    Combining GPS/INS/odometer data has been considered one of the most attractive methodologies for ground vehicle navigation. In the case of long GPS signal blockages inherent to complex urban environments, however, the accuracy of this approach is largely deteriorated. To overcome this limitation, this study proposes a novel ground vehicle navigation system that combines INS, odometer and omnidirectional vision sensor. Compared to traditional cameras, omnidirectional vision sensors can acquire much more information from the environment thanks to their wide field of view. The proposed system automatically extracts and tracks vanishing points in omnidirectional images to estimate the vehicle rotation. This scheme provides robust navigation information: specifically by combining the advantages of vision, odometer and INS, we estimate the attitude without error accumulation and at a fast running rate. The accurate rotational information is fed back into a Kalman filter to improve the quality of the INS bridging in harsh urban conditions. Extensive experiments have demonstrated that the proposed approach significantly reduces the accumulation of position, velocity and attitude errors during simulated GPS outages. Specifically, the position accuracy is improved by over 30% during simulated GPS outages. View full abstract»

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  • Super-resolution direction finding with far-separated subarrays using virtual array elements

    Publication Year: 2011 , Page(s): 824 - 834
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (689 KB)  

    In this study, a novel two-stage virtual array element construction procedure is proposed for super-resolution direction finding of multiple narrowband coherent point sources with a sparse array consisting of two or more far-separated subarrays. An all-pole model is used to fit to the array snapshot and the corresponding model parameter estimation methods are discussed. Virtual elements between and outside the subarrays are then constructed in sequence using different approaches, namely, the semi-parametric and non-parametric techniques, to increase the effective array aperture size. As a result, a great improvement in angular resolution is achieved. Compared with the existent procedure using minimum weighted norm (MWN) only, the proposed procedure is superior in sidelobe artefact reduction and weaker adjacent source detection as a result of its inherent low sidelobe level. Numerical simulations also demonstrate that under lower signal-to-noise ratio or with fewer snapshots, the proposed procedure has better performance than the one using MWN only in both resolution and accuracy, as well as the conventional estimation of signal parameters via rotational invariance techniques in accuracy, although such advantages tend eventually to disappear with reduced target angular spacing. View full abstract»

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  • Semantic labelling of SAR images with conditional random fields on region adjacency graph

    Publication Year: 2011 , Page(s): 835 - 841
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (767 KB)  

    Scene segmentation and semantic labelling are important for analysing and understanding synthetic aperture radar (SAR) images. In this study, the authors propose an effective and efficient labelling method for SAR images with conditional random fields on a region adjacency graph (CRF-RAG). More precisely, for an SAR image, a region adjacency graph (RAG) representation is firstly built on an initially over-segmentation of the image. Subsequently, a conditional random field (CRF) model is established over the RAG instead of over pixels. To train and infer the CRF-RAG model, a fast max-margin training strategy and the graph cut optimisation method are finally employed. As the CRF model is based on RAG, the computation complexity of the model can be reduced significantly. Compared to the Markov random field (MRF) model on RAG, the proposed CRF-RAG model is more efficient to incorporate different measures of SAR images, such as scattering intensity, texture and image context, into a unified model. Experiments on the TerraSAR-X imagery achieve promising results with modest computation cost, which validates the generality and flexibility of the proposed method. View full abstract»

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  • Beamforming with distortionless co-polarisation for conformal arrays based on geometric algebra

    Publication Year: 2011 , Page(s): 842 - 853
    Cited by:  Papers (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1005 KB)  

    This study presents a general and systematic method for three-dimensional pattern analysis and beamforming with distortionless co-polarisation for arbitrary conformal arrays. The method is based on the mathematical framework of geometric algebra and is able to consider element patterns which are both directional and polarised to produce a compact representation of the array pattern. As well as being simpler and more direct than derivations in the current literature, the method provides a visually intuitive means of dealing with the many frame conversions necessary in conformal array analysis. Geometric algebra provides us with an analysis tool, which is simpler and more practical than the traditional Euler rotation and matrix representations. Here a space-polarisation filter based on a conventional delay-and-sum structure is proposed for the pattern beamforming for conformal arrays. Filters assigned to each antenna are used to acquire the overall array pattern and the authors use the co-polarisation component to realise beamforming. In addition to the new derivation, the authors compare with traditional methods and present simulations on a cylindrical conformal array. View full abstract»

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  • Novel atomic decomposition algorithm for parameter estimation of multiple superimposed gaussian chirplets

    Publication Year: 2011 , Page(s): 854 - 861
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (583 KB)  

    Atomic decomposition (AD) is an adaptive approximation technique that provides a sparse, flexible and physically meaningful representation of signals. Gaussian chirplet is suitable to represent radar signals because linear-frequency modulation is very common for radar signals and chirplet exhibits good time-frequency concentration. Thus, the application of AD, for complex radar emitter detection and estimation, has been extensively investigated. To overcome the resolution problem and the `overfitting` phenomenon caused when previous AD algorithms are used to deal with multiple chirplets that are partially superimposed in the time domain, a novel algorithm using the subspace orthogonal matching pursuit technique is presented in this study. This algorithm can also obtain higher parameter estimation accuracy, compared with other commonly employed AD algorithms, especially at low signal-to-noise ratio. Moreover, the parameter estimates can be further refined by an iterative alternating projection algorithm, which makes the estimation accuracy much closer to the Cramer-Rao bound. The simulation results illustrate the advantages of the two proposed methods. View full abstract»

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  • Investigation on accurate signal modelling and imaging of the moving target in ground-based forward scatter radar

    Publication Year: 2011 , Page(s): 862 - 870
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (407 KB)  

    The existing signal model and imaging algorithm of the moving target in the forward scatter radar (FSR) are built based on the assumptions that the baseline is long, diffraction angle is small and velocity direction of the target is approximately perpendicular to the baseline. However, the ground-based FSR system is characterised by short baseline and large diffraction angle, and the velocity direction of the target is not always perpendicular to the baseline. Therefore in many cases, the above assumptions introduce significant errors to the imaging results in the ground-based FSR. In the light of the imaging requirements of the moving target in the ground-based FSR, firstly, the current forward scatter (FS) signal model is modified using the high-order approximation method based on the Fresnel-Kirchhoff diffraction formula. The modified signal model considered the effect of high-order terms of Doppler phases, quadratic term of the target profile length, velocity direction of the target and diffraction angle changes, and therefore FS signal of the moving target in the ground-based FSR can be more precisely described. Secondly, the current imaging algorithm is modified based on the modified signal model, and the expressions applicable to precise reconstruction of the target profile in the ground-based FSR are analytically deduced. Finally, the effectiveness of the modified imaging algorithm is validated through the simulation results. View full abstract»

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  • Range-layover to height mapping in high grazing angle synthetic aperture radar for non-interferometric 3-D image formation

    Publication Year: 2011 , Page(s): 871 - 876
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (386 KB)  

    Small unmanned aircraft or other aircraft that operate at short range are likely to need to operate at steep look-down angles. Imaging at high grazing angle causes range-layover which affects synthetic aperture radar (SAR) images in the down-range direction, but not in cross-range. By making a number of images at different look angles relative to the target, the 3-D position of individual scatterers on the target can be calculated, as long as they remain visible over an appreciable angular extent. The range-layover to height mapping algorithm is presented here for forming 3-D images from high grazing angle SAR data. This algorithm only requires data collected from a single antenna and a single pass of the target to form a 3-D image. View full abstract»

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  • Multi-target state extraction for the particle probability hypothesis density filter

    Publication Year: 2011 , Page(s): 877 - 883
    Cited by:  Papers (5)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (427 KB)  

    The probability hypothesis density (PHD) filter has emerged as a promising tool for dealing with the multi-target tracking problem in recent years. However, except in some special situations, closed-form recursive update equations for the PHD filter do not exist and the particle filter approaches have to be used. The output of the particle filter at each step is the particle clouds approximation of the PHD. Thus, some special algorithms are needed to extract the target states from those particles. Utilising the information of both particles' weight and their spatial distribution, an improved algorithm named C-Clean is proposed in this study. This algorithm is comprised of two steps. First, clustering techniques are used to exploit the spatial distribution of particles. Then, within those clusters whose corresponding PHD weight is beyond some predefined threshold, the peak extraction procedure modified from the CLEAN technique is taken to extract the multi-target state. Simulation results demonstrate that its performance is better than those algorithms using the information of particles' spatial distribution or weight only. View full abstract»

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  • Scheduling for multifunction radar via two-slope benefit functions

    Publication Year: 2011 , Page(s): 884 - 894
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (452 KB)  

    The scheduling of tracking and surveillance looks for multifunction radar is considered. A technique called the sequential scheduler is proposed, whereby tracking looks and high-priority surveillance looks are scheduled first, and lower-priority surveillance looks are then scheduled to occupy gaps in the radar time line. A method called the two-slope benefit function (TSBF) sub-scheduler is used and requires that each tracking look and high-priority surveillance look has a benefit function, which specifies benefit as a function of start time. This method accounts for both look priority and target dynamics in formulating a look schedule. If the radar is overloaded with tracking look requests, the TSBF sub-scheduler down-selects a set of looks that can be scheduled, using a method that favours higher priority looks. Looks are scheduled to maximise the total benefit, and it is shown that the resulting maximisation is equivalent to a linear program which can be solved efficiently using the simplex method. A technique called the gap-filling sub-scheduler is used to schedule lower-priority surveillance looks. An example is presented which illustrates the properties of the sequential scheduler. View full abstract»

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  • Highly dispersive scattering centre analysis using an enhanced parametric model

    Publication Year: 2011 , Page(s): 895 - 901
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (319 KB)  

    The existing dispersive scattering centre (DSC) models characterise high frequency backscatter of targets for range profile analysis. These models fail to analyse the inherent non-point scatterers such as highly dispersive waveguide geometries with a large number of propagation modes. Here, a parametric model is proposed that represents such misbehaved DSC as a sum of few equivalent point scatterers using an auxiliary correcting dispersion factor that gets around modal analysis. A population-based maximum likelihood algorithm is utilised to estimate the unknown parameters. The high-spatial resolution PRONY method is utilised for initialisation of some parameters. Measurements and method of moment solutions of some canonical and non-canonical dispersive targets are used in the authors' parameter estimation. Comparisons are made with the inverse fast Fourier transform (IFFT) results. View full abstract»

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  • Imaging moving targets using the second-order keystone transform

    Publication Year: 2011 , Page(s): 902 - 910
    Cited by:  Papers (3)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (434 KB)  

    The use of synthetic aperture radar (SAR) for moving target imaging has recently attracted a great deal of interest. The ability to obtain focused images of moving targets makes it possible to maximise the use of existing single-channel SAR systems, without upgrading to more complex and expensive multi-channel systems. In this study, a novel technique is presented for moving target imaging utilising a single-channel SAR operating in Spotlight mode. First, the second-order keystone transform is applied to remove range curvature. Next, a non-linear phase correction is applied to correct the remaining range walk. Finally, the nominally quadratic phase in azimuth is estimated and corrected to provide focused imagery. An experimental result is presented to demonstrate the performance of this approach. View full abstract»

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Aims & Scope

IET Radar, Sonar & Navigation covers the theory and practice of systems involving the processing of signals for radar, radiolocation, radionavigation and surveillance purposes.

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