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Radar, Sonar and Navigation, IEE Proceedings -

Issue 4 • Date Aug 2001

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Displaying Results 1 - 7 of 7
  • Frequency and noise dependence of the image reconstruction of ground surfaces using the conjugate gradient based algorithm

    Page(s): 211 - 218
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (872 KB)  

    It has been shown previously that the ground surface of the Earth can be imaged using radio ground waves with antennas positioned on the ground surface. The image of the surface is obtained by reconstructing the distribution of the normalised surface impedance of the surface from the measurements of the scattered fields at a number of positions around the surface being imaged with electromagnetic radiation from different azimuthal directions. It has also been shown that the inverse problem can be solved iteratively using a conjugate gradient method and the images of ground surfaces can be produced using the noiseless data of the measured scattered fields at an operating frequency at which the size of the surface is approximately one wavelength. In practice, the image reconstruction depends on the operating frequency, and the measured scattered fields are subject to white noise and measurement errors. The dependence of the image reconstruction using the conjugate gradient method on the operating frequency and noise in the measured data is thus studied and the results of reconstruction errors at different frequencies and signal-to-noise ratios and the reconstructed images are presented. It is shown that the image reconstruction using the conjugate gradient based algorithm has a strong dependence on the operating frequency and noise. However, the algorithm is able to reconstruct the images of ground surfaces in a small number of iterations when the signal-to-noise ratio is greater than 12 dB View full abstract»

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  • Robust adaptive array beamforming with random error in cycle frequency

    Page(s): 193 - 199
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (644 KB)  

    By exploiting cyclostationary properties, the SCORE algorithms presented by Agee et al. (1990) have been shown to be effective in performing adaptive beamforming without requiring the direction vector of the desired signal. However, these algorithms suffer from severe performance degradation in the presence of a random error in cycle frequency. The authors first establish a statistical model of the cyclic correlation matrix when the random error exists. According to this statistical model, two robust methods based on the SCORE algorithms are developed to achieve robust adaptive beamforming against random error. Analytical formulas are then derived for evaluating the performance of the proposed methods. Several simulation examples are also presented for confirming the theoretical analysis and showing the effectiveness of the proposed methods View full abstract»

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  • Optimisation and sensitivity analysis of GPS receiver tracking loops in dynamic environments

    Page(s): 241 - 250
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (832 KB)  

    For a GPS receiver, decreasing the receiver tracking loop bandwidth reduces the probability of loss of lock if there are no vehicle dynamics. However, reduced bandwidth increases tracking errors due to dynamics. Beyond a certain limit it causes a serious degradation in the dynamic tracking performance. Therefore, there is involvement of a tradeoff between two opposing considerations: narrow tracking loop bandwidths are desired for filtering noise due to thermal effects, but wide tracking loop bandwidths are desired to permit tracking of vehicle dynamics. Optimal tracking loop bandwidths, which yield the minimum errors in a certain dynamics environment, are first investigated. The linear Kalman filter is employed as the optimal estimator. The covariance for the arbitrary gain model is solved and applied to the sensitivity analysis for investigating error growth due to incorrect noise level estimates. Theoretical results are verified by numerical simulation, and results from both approaches are in very good agreement View full abstract»

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  • Maximum likelihood approach to the detection of changes between multitemporal SAR images

    Page(s): 200 - 210
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (3044 KB)  

    The authors introduce maximum likelihood techniques for optimised discrimination between agricultural and wooded regions, based on a multitemporal sequence of ERS images. The inherent resolution of the system is inadequate to make such a classification on an individual image. However, the different temporal change patterns of the two classes can be exploited. One approach uses joint annealed segmentation of the image sequence, providing optimised exploitation of the speckle model in determining the common set of region boundaries in the underlying radar cross-section. This is followed by maximum likelihood change detection using a normalised log temporal texture measure. This is shown to be superior to constructing the normalised log measure directly including speckle fluctuations, followed by a single annealed segmentation process. Finally, it is demonstrated how simple filtering of this normalised log measure can provide reasonable classification with greatly reduced computation load View full abstract»

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  • Development of a statistical procedure for detecting the number of signals in a radar measurement

    Page(s): 219 - 226
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (944 KB)  

    Ranking and selection theory is applied to the eigenvalue problem. Of concern is the development of a procedure for computing the number of signals in a measurement data vector. In the authors' approach, the multiplicity of the noise eigenvalue is computed, and used in calculating the number of non-noise (signal) eigenvalues View full abstract»

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  • Robust CFAR detection of random signals in compound-Gaussian clutter plus thermal noise

    Page(s): 227 - 232
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (612 KB)  

    An algorithm for detecting a random target signal against a mixture of correlated compound-Gaussian clutter and white Gaussian thermal noise is proposed. The new detection strategy is obtained by extending the generalised matched subspace detector previously derived by Gini and Farina (1999) for only compound-Gaussian clutter. Two different versions of the detection strategy are proposed and compared: the first relies on the estimation of the radar clutter texture component; the second trades-off performance with computational complexity by using the texture mean value in place of its estimate. The texture estimator mean square error is derived in closed form and analysed. Additionally, the robustness of the detector false alarm rate to changes of clutter parameters and the detection performance are numerically investigated by Monte Carlo simulation View full abstract»

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  • Microwave detection of buried mines using non-contact, synthetic near-field focusing

    Page(s): 233 - 240
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1292 KB)  

    Existing ground penetrating radars (GPR) are limited in their 3-D resolution. For the detection of buried land-mines, their performance is also seriously restricted by `clutter'. Previous work by the authors has concentrated on removing these limitations by employing multi-static synthetic focusing from a 2-D real aperture. This contribution presents this novel concept, describes the proposed implementation, examines the influence of clutter and of various ground features on the system's performance, and discusses such practicalities as digitisation and time-sharing of a single transmitter and receiver. Experimental results from a variety of scenarios are presented View full abstract»

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Aims & Scope

IEE Proceedings Radar, Sonar and Navigation covers the theory and practice of systems involving the processing of signals for radar, radio location, radio navigation and surveillance purposes.

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