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Radar, Sonar and Navigation, IEE Proceedings -

Issue 1 • Date Feb 2000

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Displaying Results 1 - 6 of 6
  • Translation to the normal distribution for radar clutter

    Page(s): 17 - 22
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (576 KB)  

    The single point statistics of some high-resolution low-grazing angle radar sea clutter are examined. Three different distributions are used to model the cumulative density of the data. The Weibull and the K-distribution both require the addition of a Rayleigh distributed component to give a good fit to the data. This Rayleigh distributed component has a mean level significantly higher than the thermal noise level. A third model, the `sinusoidal bound system' (sin SB) is also developed. It performs very well in fitting the extremes of the cumulative distribution, particularly the upper limit, which is not well fitted by the other models View full abstract»

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  • Joint super-resolution moving target feature extraction and stationary clutter suppression

    Page(s): 23 - 29
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (576 KB)  

    High range resolution (HRR) moving target indicator radar is becoming increasingly important for many military and civilian applications involving the detection and classification of moving targets within a clutter background. For ground-based HRR radar, when targets are moving slowly or near-broadside and the coherent processing interval or dwell time is not too long, the effects of range migration and range feature distortion can be ignored. Based on this assumption, relaxation-based algorithms that are robust and computationally simple are proposed for HRR feature extraction of moving targets consisting of scatterers closely spaced in range in the presence of stationary clutter. Numerical examples show that the proposed algorithms exhibit super-resolution and excellent estimation performance View full abstract»

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  • Slant range and cross range correction for polar format distortion in ISAR imaging

    Page(s): 2 - 8
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (512 KB)  

    The authors describe a focusing procedure, for use in step-frequency ISAR imaging, which corrects for the assumption of a rectangular data sampling grid; searches for focused images can be shortened using a two stage procedure. The first stage of processing constructs an intermediate image from which slant range blurring is removed, The second stage removes the slant range dependent, cross range blurring by phase correction of the slant range profile. Example images using simulated data are used to illustrate results from each stage of the processing. An example using experimental data is also shown View full abstract»

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  • Robust blind beamforming using neural network

    Page(s): 41 - 46
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (400 KB)  

    Many blind beamforming algorithms, such as constrained cyclic adaptive beamforming (C-CAB), use cyclostationarity to estimate the steering vector and adaptively obtain the linearly constrained minimum variance (LCMV) optimum solution. However, LCMV methods are sensitive to the mismatch caused by the uncalibration array or estimate error. After discussion of this mismatch, a robust blind beamforming algorithm is presented. Implemented as a neural network, this algorithm reduces the computational complexity for real-time use. Computer simulations verify the analysis View full abstract»

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  • Simulation of CFAR detection algorithms for arbitrary clutter distributions

    Page(s): 31 - 40
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (716 KB)  

    Simulation and performance estimation methodologies are developed for constant false-alarm rate (CFAR) detection algorithms based on the powerful concept of importance sampling (IS). Such algorithms involve crossings of a random threshold. Compression of the threshold density function produces the required biasing to implement IS procedures. Adaptive optimisation of simulation estimators and estimation of detector threshold multipliers are described. Easily computable approximations for false-alarm probabilities (FAPs) of cell averaging (CA)-CFAR detectors are derived. Fast simulation results are described for examples with known clutter distributions. The practically important situation when clutter densities are unknown is dealt with. Algorithms blind to the density and having appreciable gains over conventional Monte Carlo simulation are demonstrated. In a limited experiment these are shown to track a step change in clutter distribution. It is argued, albeit tentatively, that the procedures could point the way to implementation of estimators for FAPs and their control through threshold adaptation View full abstract»

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  • Target detection in correlated SAR clutter

    Page(s): 9 - 16
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (772 KB)  

    Synthetic aperture radar (SAR) clutter may be characterised by its single-point statistics and its correlation structure, both of which should be exploited in applications such as target detection. The non-Gaussian distributions associated with SAR clutter can be incorporated in detection schemes based on single-point statistics in a reasonably straightforward manner. However, use of the correlation structure is hampered by the difficulties associated with analytical manipulation of correlated non-Gaussian distributions. A generic model for correlated radar clutter is proposed based on a correlated Gaussian mixture distribution approximation to the clutter statistics in the log domain. Analytical manipulation of the model is possible because it is based on weighted sums of multivariate Gaussian distributions which have a tractable closed-form representation. The improved target detection performance which results from this approach is demonstrated 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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