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Radar, Sonar and Navigation, IEE Proceedings -

Issue 1 • Date Feb 1999

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Displaying Results 1 - 9 of 9
  • Improved particle filter for nonlinear problems

    Page(s): 2 - 7
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (568 KB)  

    The Kalman filter provides an effective solution to the linear Gaussian filtering problem. However where there is nonlinearity, either in the model specification or the observation process, other methods are required. Methods known generically as `particle filters' are considered. These include the condensation algorithm and the Bayesian bootstrap or sampling importance resampling (SIR) filter. These filters represent the posterior distribution of the state variables by a system of particles which evolves and adapts recursively as new information becomes available. In practice, large numbers of particles may be required to provide adequate approximations and for certain applications, after a sequence of updates, the particle system will often collapse to a single point. A method of monitoring the efficiency of these filters is introduced which provides a simple quantitative assessment of sample impoverishment and the authors show how to construct improved particle filters that are both structurally efficient in terms of preventing the collapse of the particle system and computationally efficient in their implementation. This is illustrated with the classic bearings-only tracking problem View full abstract»

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  • State estimation of short-range target with multisensors

    Page(s): 8 - 16
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (604 KB)  

    The optimal estimation method is systematically investigated for estimating the position and velocity vectors of a short-range target in space with a multisensor system TRn (one transmitting sensor and n receiving sensors). First, the relation between the coherent centralised processing (CP) and decentralised processing (DP) is discussed. After showing that the performance of DP and CP procedures are asymptotically identical, in the sense that the observation time approaches infinity, the Cramer-Rao lower bound (CRLB) for the DP estimator is given. Then a suboptimal and realisable signal processing scheme is provided. The performance of the suboptimal procedure is analysed theoretically in detail, and analytical expressions are obtained for the covariance matrix of the estimator error. Simulation results verify the theoretical predictions. This demonstrates that the system is able to accurately locate a short-range target View full abstract»

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  • One-dimensional fractal model of the sea surface

    Page(s): 55 - 64
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (940 KB)  

    A one-dimensional fractal model of the sea surface based on the band-limited Weierstrass-Mandelbrot fractal functions is proposed. The model accounts for the geometry and time dependence of the sea surface shape and is in agreement with the solution of the sea hydrodynamic differential equations obtained in a linear regime. A statistical analysis electromagnetic field scattered from the fractal surface is performed to validate the model from the scattering phenomenon point of view. The results are in good agreement with experimental results presented in the literature View full abstract»

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  • Effects of user distribution on CDMA antenna array receivers

    Page(s): 25 - 30
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (572 KB)  

    The use of sectorised antenna array receivers for the uplink of cellular code division multiple access systems is discussed. The distribution of users in the sector can seriously alter the sector capacity that can be achieved. The authors consider two algorithms, matched filtering and interference suppression, and their performance for different user distributions. Simulation results are presented to show the effect of user clustering on system performance for a number of different scenarios View full abstract»

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  • Radar detection in multipath

    Page(s): 45 - 54
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (688 KB)  

    An analysis of the detection of radar targets in multipath environments is presented. Radar targets often undergo enhancements or fades due to multipath where the direct-path energy combines with a phase-shifted reflection to enhance or reduce the received energy. This phenomenon is a function of frequency. Radars are often designed to avoid the problems of fades by changing frequency or using an assortment of frequencies in an M-out-of-N detector. To understand the detection statistics and choose M and N, the probability density function (PDF) of the noise plus the target times the multipath propagation factor must be known. This PDF is derived for a nonfluctuating target and for a Rayleigh target. The PDF is used to show the benefits of choosing the best M for a multipath environment compared to using the M that would be chosen in a free-space environment View full abstract»

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  • Novel method for super-resolution in radar range domain

    Page(s): 40 - 44
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (360 KB)  

    A method based on adaptive regularisation for range super-resolution is presented. The method is computationally efficient and has low SNR threshold close to that of the maximum likelihood (ML) method. The method can simultaneously estimate the number and time delays of the overlapping echoes, whereas determining the number of echoes in ML-type algorithms is difficult. Numerical simulation results demonstrate the performance and show that the method is capable of simply and effectively achieving enhanced range resolution View full abstract»

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  • Performance of corrected adaptive monopulse estimation

    Page(s): 17 - 24
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (692 KB)  

    The shape of sum and difference beams can be severely distorted if nulls in jammer directions are formed. In a previous paper a correction formula was developed that can be applied to monopulse estimation with subarray output adaptive arrays as well as to generalised sidelobe canceller (GSLC) configurations. The present paper derives the probability density function for such monopulse estimators with given adaptive beams for Rayleigh targets and jammers. With this both mean and variance can be easily calculated. For nonfluctuating targets and Gaussian jammers formulas for the mean and variance are given which have to be evaluated numerically. These results can be used to analyse the performance of different corrected adaptive monopulse schemes. In particular it is demonstrated how the bias and variance of the monopulse estimates depend on jammer location, SNR, type and number of subarrays or auxiliary channels for the GSLC View full abstract»

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  • Sidescan sonar: a directional filter of seabed texture?

    Page(s): 65 - 72
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1044 KB)  

    As the exploration of the seafloor is extended ever further, automated classification and interpretation of sonar images are becoming increasingly important. However, many of the image processing techniques employed for these purposes consider the images simply as a collection of textures and neglect the process by which these images are formed. The most important aspect thus neglected is the directionality of the imaging process and its subsequent effect on the image textures produced. The paper reports the results of a systematic investigation of the effect of the sonar process on image texture directionality, illustrating the importance of the relative orientation of the sonar and the seabed features during the sonar image capture process. A frequency domain model is developed for examining and quantifying these orientation effects, and the subsequent effect on a classification system is demonstrated View full abstract»

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  • Optimal observer trajectory in bearings-only tracking for manoeuvring sources

    Page(s): 31 - 39
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (784 KB)  

    In the bearings-only tracking context, the source state is only partially observed through nonlinear measurements which are the estimated bearings. For a manoeuvring Markovian source, the source trajectory is estimated by means of classical dynamic programming. However, the quality of the estimation is strongly dependent of the observer trajectory, thus mixing estimation and control. But, in this context, the separation principle (for estimation and control) does not hold. In fact, the problem consists in controlling a partially observable Markov decision process. Application of this framework to search theory is mentioned. However, even if the problem presents strong similarities with an approach used in the optimisation of the search effort for a (Markovian) moving source, it is focused on the estimation of the whole source trajectory instead of its detection at the end of the scenario. To this intrinsic difficulty, the observation is richer. Consequently also, the optimisation problem presents important difficulties, i.e. memory and computation requirements. Thus the authors aim to develop a feasible framework, based on the Smallwood and Sondik (1973) approach, capable of handling real problems. To attain this objective, a specific algorithm is developed and the dimension of the bearings-only tracking is drastically reduced. The applicability of the approach is demonstrated on realistic sonar scenarios. 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.

Full Aims & Scope