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Online ISSN 1751-8792 Print ISSN 1751-8784

IET Radar, Sonar & Navigation

Volume 2, Issue 2, April 2008

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Volume 2, Issue 2

April 2008

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    • Motion error correction of range migration algorithm for aircraft spotlight SAR imaging
      • Author(s): H.-S. Shin  and  J.-T. Lim
      • Source: IET Radar, Sonar & Navigation, Volume 2, Issue 2, p. 79 –85
      • DOI:  10.1049/iet-rsn:20070018
      • Type: Article
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      • p. 79 –85 (7)
        Since a motion error is the main phase error source in the aircraft synthetic aperture radar, several reconstruction algorithms with motion error correction have been developed. An efficient motion compensation via the known motion error information is proposed. Specifically, the proposed method is based on the subarea technique with shifting and the subaperture technique via the mean values of the motion errors. Then, using the extended Taylor approximation and the principle of the stationary phase, the motion errors are corrected through compensation at the mixing stage and the Stolt interpolation stage.
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      Temporal coherent adaptive target detection for multi-input multi-output radars in clutter
      • Author(s): A. Sheikhi  and  A. Zamani
      • Source: IET Radar, Sonar & Navigation, Volume 2, Issue 2, p. 86 –96
      • DOI:  10.1049/iet-rsn:20070024
      • Type: Article
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      • p. 86 –96 (11)
        The superiority of multiple-input multiple-output (MIMO) radars over conventional phased-array radars has been recently shown in many aspects. The MIMO radars have better detection performance and can extract target information more precisely than phased-array radars. The problem of adaptive target detection using temporal coherent pulse train in the presence of nonhomogeneous clutter (different clutter statistics in receivers) is considered for MIMO radars. This problem has been formulated as a hypothesis test. For clutter with unknown statistics three adaptive decision rules have been developed using the generalised likelihood ratio test. The results show the superiority of the MIMO radars with temporal coherent processing over conventional phased arrays in the presence of clutter.
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      Azimuth dependence of Doppler spectra of sea clutter at low grazing angle
      • Author(s): T. Lamont-Smith
      • Source: IET Radar, Sonar & Navigation, Volume 2, Issue 2, p. 97 –103
      • DOI:  10.1049/iet-rsn:20070099
      • Type: Article
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      • p. 97 –103 (7)
        The effect of varying the azimuth angle of a cliff-top radar on the Doppler spectra of low grazing angle sea clutter has been investigated. The peak of the horizontally polarised Doppler spectra was found to depend on the component of the phase velocity of the breaking waves in the line of sight of the radar. The analysis was presented in terms of two main scattering components, one slow and one fast, which could explain the Doppler spectra as well as the higher moments of the spectra. The connection to the amplitude statistics for the two components was also discussed. The slow component was present all the time and had amplitude statistics that were Rayleigh-distributed. The fast component was present only intermittently and had amplitude statistics that were spikier than the Rayleigh distribution. The width of the spectra varied with azimuth in a way unrelated to the direction relative to the wind. A wave tank experiment with long wavelength mechanical waves and wind-generated waves illustrated that the cause of the broadening of the spectra was probably due to the effect of swell waves.
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      Adaptive update interval tracking based on adaptive grid interacting multiple model
      • Author(s): T. Cheng ; Z. He ; T. Tang
      • Source: IET Radar, Sonar & Navigation, Volume 2, Issue 2, p. 104 –110
      • DOI:  10.1049/iet-rsn:20070094
      • Type: Article
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      • p. 104 –110 (7)
        The update interval is adjustable in the phased array radar system. An adaptive update interval algorithm based on the adaptive grid interacting multiple model is proposed. The moving step size of mid-model's parameter is utilised to adapt the update interval to the target's behaviour. Furthermore, a controllable parameter is introduced to balance the tracking precision and the system load. The effectiveness of the algorithm is verified through simulation. The simulation results also demonstrate that the proposed algorithm can save much system resource while achieving the same tracking quality as the fixed update interval algorithm.
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      Likelihood ratio test-based interval estimate of the number of signals present in a measurement
      • Author(s): P. Chen ; J.S. Markow ; M.C. Wicks
      • Source: IET Radar, Sonar & Navigation, Volume 2, Issue 2, p. 111 –120
      • DOI:  10.1049/iet-rsn:20060050
      • Type: Article
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      • p. 111 –120 (10)
        A multi-step procedure is proposed to construct a confidence interval for the number of signals present and a comparative analysis of our procedure with other existing procedures is conducted. The proposed procedure uses likelihood ratio statistics and its simulated percentiles sequentially to determine the upper and lower limits for the confidence interval. A preference zone in the parameter space of the population eigenvalues is defined and it is used to separate the signals and the noise. The least favourable configuration (LFC) is derived asymptotically under the preference zone. Under the LFC, the procedure parameters necessary to attain the required confidence level are determined. A comparative analysis with other procedures is presented in tables.
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      Sweep signal time-delay estimation with time–frequency cross-correlation algorithm
      • Author(s): Z.J. Jiang  and  T.J. Cui
      • Source: IET Radar, Sonar & Navigation, Volume 2, Issue 2, p. 121 –126
      • DOI:  10.1049/iet-rsn:20070076
      • Type: Article
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      • p. 121 –126 (6)
        Sweep signal is usually employed as a source signal in active detection such as radar and sonar. Since the frequency spectrum of the sweep signal varies against time, a novel algorithm, namely a time–frequency cross-correlation (TFCC) algorithm based on wavelet packet transform (WPT), is proposed to estimate the time delay of sweep signal. In this algorithm, the source sweep and the received signals are decomposed with WPT to obtain their time–frequency representations and the TFCC between the source sweep and the received signals is performed. Each reflected sweep in the received signal is converted into a time–frequency correlation peak whose position can indicate its time delay. The TFCC algorithm can suppress ambient noise effectively and improve the performance of sweep extraction and can match more precisely the source and the reflected sweeps to their known time–frequency characters. Numerical experiments were performed to compare the performance of the TFCC algorithm with that of the conventional cross-correlation and phase-data algorithms. The results proved that the TFCC algorithm can extract the reflected sweeps effectively and its performance is better than that of the conventional algorithms.
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      Direction-finding of coherent sources via ‘particle-velocity-field smoothing’
      • Author(s): J. Tao ; W. Chang ; Y. Shi
      • Source: IET Radar, Sonar & Navigation, Volume 2, Issue 2, p. 127 –134
      • DOI:  10.1049/iet-rsn:20050140
      • Type: Article
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      • p. 127 –134 (8)
        A new ‘particle-velocity-field smoothing’ (PVFS) algorithm is proposed to decorrelate up to three coherent sources for azimuth-elevation direction-finding using vector-hydrophones in the underwater acoustic medium. The coherency among the incident sources would reduce the data correlation matrix's rank to below the number of incident sources, but this proposed algorithm restores the rank by summing the individual particle-velocity-field component's data correlation matrices. This scheme uses identically oriented underwater-acoustic vector-hydrophones, its locations may be arbitrary. Each underwater-acoustic vector-hydrophone consists of two or three collocated but orthogonally oriented velocity-hydrophones, and a pressure-hydrophone. In contrast to the customary ‘spatial smoothing’ technique, this proposed PVFS algorithm does not reduce the array's spatial aperture and does not require any ‘virtual array interpolation’ even for an irregularly shaped array grid. Monte Carlo simulations verify this proposed scheme's efficacy.
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      Feature-based human motion parameter estimation with radar
      • Author(s): P. van Dorp  and  F.C.A. Groen
      • Source: IET Radar, Sonar & Navigation, Volume 2, Issue 2, p. 135 –145
      • DOI:  10.1049/iet-rsn:20070086
      • Type: Article
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      • p. 135 –145 (11)
        Radar can be an extremely useful sensing technique to observe persons. It perceives persons behind walls or at great distances and in situations where persons have no or poor visibility. Human motion modulates the radar signal which can be observed in the spectrogram of the received signal. Extraction of these movements enables the animation of a person in virtual reality. The authors focus on a fast feature-based approach to estimate human motion features for real-time applications. The human walking model of Boulic is used, which describe the human motion with three parameters. Personification information is obtained by estimating the individual leg and torso parameters. These motion parameters can be estimated from the temporal maximum, minimum and centre velocity of the human motion distribution. Three methods are presented to extract these velocities. Additionally, we extract an independent human motion repetition frequency estimate based on velocity slices in the spectrogram. Kalman filters smooth the parameters and estimate the global Boulic parameters. These estimated parameters are input to the human model of Boulic which forms the basis for animation. The methods are applied to real radar measurements. The animated person generated with the extracted parameters provides a realistic look-alike of the real motion of the person.
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      Adaptive fusion framework based on augmented reality training
      • Author(s): P.-Y. Mignotte ; E. Coiras ; H. Rohou ; Y. Pétillot ; J. Bell ; K. Lebart
      • Source: IET Radar, Sonar & Navigation, Volume 2, Issue 2, p. 146 –154
      • DOI:  10.1049/iet-rsn:20070136
      • Type: Article
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      • p. 146 –154 (9)
        A framework for the fusion of computer-aided detection and classification algorithms for side-scan imagery is presented. The framework is based on the Dempster–Shafer theory of evidence, which permits fusion of heterogeneous outputs of target detectors and classifiers. The utilisation of augmented reality for the training and evaluation of the algorithms used over a large test set permits the optimisation of their performance. In addition, this framework is adaptive regarding two aspects. First, it allows for the addition of contextual information to the decision process, giving more importance to the outputs of those algorithms that perform better in particular mission conditions. Secondly, the fusion parameters are optimised on-line to correct for mistakes, which occur while deployed.
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