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Radar, Sonar & Navigation, IET

Issue 3 • Date March 2011

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Displaying Results 1 - 18 of 18
  • Cross-correlation performance assessment of global positioning system (GPS) L1 and L2 civil codes for signal acquisition

    Page(s): 195 - 203
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (840 KB)  

    Owing to imminent availability of global positioning system (GPS) L2C full constellation, low-cost dual-frequency GPS L1/L2C receivers are likely to appear on the market in the near future. The L1 C/A, L2 CM and L2 CL are the code choices available to combat the `near-far` problem in such a receiver. The published average cross-correlation protection figures of these codes (C/A: 22 dB, CM: 28 dB and CL: 45 dB) are not sufficient to determine the right code choice for different acquisition scenarios. The aim of this study is to evaluate the robustness of each code to the near`far problem and develop recommendations for code/frequency selection in a given acquisition scenario. For comparison of L2C and C/A codes, multiple C/A periods are to be considered, in order to be consistent with the signal observation interval. It is shown that the cross-correlation performance of multiple C/A periods is strongly dependent on the relative Doppler offset between local and interfering signals, and consequently it is much superior to that of the single C/A period. It is concluded that the C/A code is more robust to the near`far problem in the assisted acquisition scenarios including warm start, hot start, assisted-GPS and reacquisition, whereas L2 CM is the best code choice for the cold startup. View full abstract»

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  • Signal fusion-based target detection algorithm for spatial diversity radar

    Page(s): 204 - 214
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (653 KB)  

    Signal fusion-based radar target detection algorithms are studied in this article for spatial diversity multiple input multiple output (MIMO) radar based on the generalised likelihood ratio test (GLRT) algorithm, under the assumption that covariance matrices of clutter signals received by different radar sites are different. Two signal fusion-based target detection algorithms are proposed, which can be applied in signal fusion networks (SFNs) with typical structures, at a low communication and computation cost. Simulation experiments in several scenarios indicate that two proposed signal fusion algorithms have better detection performances than decision fusion algorithms. View full abstract»

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  • Ionosphere-corrected range estimation in dual frequency global navigation satellite systems receivers

    Page(s): 215 - 224
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1009 KB)  

    In global navigation satellite systems (GNSSs), the measurement of the satellite-receiver pseudorange requires the estimation of signal's delay. Because the accuracy of the latter affects significantly the accuracy of the final position, it is essential to consider the effect of various error sources. Ionosphere is commonly regarded as one of the most influential sources because of the fact that it can significantly delay the signal; therefore it is of paramount importance to mitigate its effects. In theory, a dual-frequency receiver can virtually eliminate the ionospheric effects if higher order effects are ignored. Although such an advantage has been widely recognised in the literature, the effect of the tracking error in the ionospheric correction and inherently on the range estimation is yet to be studied. In this study, the authors investigate the effect of tracking error on the ionosphere-corrected range in dual-frequency receivers and compare the performance of the traditional approach with least square (LS) and constrained LS methods, as well as with a new method for range estimation, proposed by the authors. The results showed that the traditional and LS methods perform well only under the restriction of zero tracking error, whereas the authors' method has the best average performance. View full abstract»

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  • Joint sensor localisation and target tracking in sensor networks

    Page(s): 225 - 233
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (639 KB)  

    The authors propose a sequential quasi-Monte Carlo (SQMC)-based algorithm for joint estimation of sensor-node locations and target trajectory in a wireless sensor network. The sensor nodes are randomly deployed with no prior knowledge about their positions. A predictive entropy-based information utility is used to select the leader node at each stage, and all other nodes are kept in standby mode to save power. The Bayesian estimates required to track the systems's nonlinear dynamics are computed using the powerful SQMC method, which naturally integrates sensor collaboration with optimal leader node selection. Extensions of the algorithm to other interesting scenarios such as missing observations and non-Gaussian noise are also presented, which are very relevant to the unreliable environments encountered in hostile territories. The authors demonstrate through simulations that even with a very small fraction of the total number of nodes acting as beacon nodes, the proposed method can not only track the moving target, but can also obtain fairly accurate estimates of the (unknown) locat p(z(t)|z(i(j))(t - 1))ions of the sensor nodes. View full abstract»

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  • Combining the interacting multiple model method with particle filters for manoeuvring target tracking

    Page(s): 234 - 255
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1338 KB)  

    Target tracking is an element of systems that performs tasks such as surveillance, navigation, aviation and obstacle avoidance. It is generally difficult to represent different behavioural aspects of the motion of a manœuvring target with a single model. Therefore multiple model-based approaches are usually required when seeking solutions for manœuvring target tracking problems, which are generally non-linear. In the recent years, new strategies have been developed via the combination of the interacting multiple model (IMM) method and variants of particle filters (PFs). The former accounts for mode switching, while the latter account for non-linearity andœor non-Gaussianity in the dynamic system models for the posed problems. This paper considers an IMM algorithm for tracking three-dimensional (3D) target motion with manœuvres. The proposed algorithm comprises a constant velocity model, a constant acceleration model and a 3D turning rate (3DTR) model. A variety of combinations of extended Kalman filters (EKFs), unscented Kalman filters (UKFs) and PFs are used for the models. The proposed IMM algorithm variants are applied to a problem on the 3D manœuvring target tracking. Simulation test results show that by using a computationally economical PF in the 3DTR model, with EKFs andœor UKFs in the remaining models, superior performance in state estimation can be achieved at relatively modest computational costs. View full abstract»

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  • Multiple-input multiple-output radar search strategies for high-velocity targets

    Page(s): 256 - 265
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (466 KB)  

    The radar detection of high-velocity targets with a multiple-element antenna array is considered. The detection performance of multiple-input multiple-output (MIMO) radar with orthogonal waveforms is compared with that of a radar using a directed beam. An analytical expression for the probability of detection for a radar with a multiple-element array is derived. For high-velocity targets, the decrease in probability of detection because of the longer integration time required for MIMO radar is quantified. It is shown that for lower-velocity targets, sector search using orthogonal waveforms results has similar detection range performance to that of scanning directed beams. For higher-velocity targets, the use of scanning directed beams yields larger detection range. View full abstract»

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  • Taylor series expansions for airborne radar space-time adaptive processing

    Page(s): 266 - 278
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1186 KB)  

    Space-time adaptive processing (STAP) for range-dependent clutter rejection in airborne radar is considered. Indeed, radar antenna architectures or configurations that are different from the conventional uniform linear antenna array (ULA) and side-looking (SL) configuration have consequences on the clutter properties. The authors here investigate the use of Taylor series expansions (TSEs) of the space-time covariance matrix in the classical sample matrix inversion (SMI) STAP method in order to mitigate the range non-stationarity of the clutter and they compare it to the derivative-based updating (DBU) already proposed in the literature. The authors also propose a new algorithm based on a TSE of the clutter plus noise subspace in conjunction with the eigencanceler-based (EC) STAP, which improves the performance in term of signal-to-interference plus noise ratio (SINR) loss, compared to the DBU method. In this study, the particular cases of a ULA and a uniform circularly curved antenna (UCCA) array in SL and non-SL monostatic configurations as well as a ULA in some bistatic configurations are considered for the test and the comparison of the presented algorithms. View full abstract»

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  • Strategy of doppler centroid estimation in synthetic aperture radar

    Page(s): 279 - 287
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (886 KB)  

    Doppler centroid is an important parameter in synthetic aperture radar (SAR) image processing. Owing to measurement uncertainties, many clutter-lock algorithms are proposed to estimate the Doppler centroid. One of the factors that affect the estimation is `chirp coupling` [linear FM signal is used as transmitting signal in SAR, and this makes echoes of targets from different range bins overlap with each other at the same range bin, which could be called `chirp coupling (CHCO)`]. In broadside or lowly squint mode SAR, CHCO is often ignored. However, with large squint angle, its influence on Doppler centroid estimation will increase and even affect the final image. The azimuth-frequency shift of echoes caused by CHCO is analysed and a method proposed to calculate the threshold angle which is used to judge its influence on Doppler centroid estimation. With the help of the threshold angle, a novel strategy of Doppler centroid estimation is proposed. After theoretic analyses, simulations and experimental results are provided to demonstrate the proposed strategy of Doppler centroid estimation. View full abstract»

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  • Range autofocus for linearly frequency-modulated continuous wave radar

    Page(s): 288 - 295
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (576 KB)  

    A software-based method for estimating and compensating for chirp non-linearity in frequency-modulated continuous wave radars is described. The method is based on the phase-gradient algorithm and time-domain warping of the dechirped signal. The method is demonstrated both on typically and severely non-linear chirps. The retrospective application is demonstrated on archive radar data. View full abstract»

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  • Multi-baseline phase unwrapping algorithm based on the unscented kalman filter

    Page(s): 296 - 304
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (798 KB)  

    A new multi-baseline phase unwrapping algorithm based on the unscented Kalman filter (UKF) for SAR interferometry is proposed. This method is the result of combining a UKF with a path-following strategy and an omni-directional local phase slope estimator. This technology simultaneously performs noise filtering and phase unwrapping by an optimal data fusion approach. In addition, phase slope will be directly estimated from the sample frequency spectrum of the complex interferogram, by which the underestimation of phase slope is overcome. Results obtained with synthetic and real data validate the effectiveness of the proposed method. View full abstract»

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  • Parametric inverse synthetic aperture radar manoeuvring target motion compensation based on particle swarm optimiser

    Page(s): 305 - 314
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (477 KB)  

    Owing to the unknown high-order unstable motion, it is difficult to realise the motion compensation, that is, envelope alignment and phase auto-focusing, for inverse synthetic aperture radar (ISAR) manoeuvring targets. By modelling the envelope shifting and phase modulation into two different high-order polynomial functions against observation time, a novel parametric ISAR motion compensation method is proposed based on polynomial coefficients estimation via particle swarm optimiser (PSO). The average range profile energy and the image contrast are chosen as the fitness functions for envelope alignment and phase auto-focusing, respectively. Furthermore, the polynomial order of phase auto-focusing is chosen higher than that of envelope alignment to meet the accuracy need of phase compensation. Besides, in order to speed up the convergence and ensure that the estimated parameters converge to the global optimisation, a least-square fitting pre-processing is also proposed to determine the target motion order and initialise the best particle at first. Finally, the results based on both numerical experiments and real data are all provided to demonstrate the effectiveness of the proposed PSO-based parametric methods. View full abstract»

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  • Radar detection based on compound-gaussian model with inverse gamma texture

    Page(s): 315 - 321
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (464 KB)  

    The coherent radar detection against a background of compound-Gaussian clutter with inverse gamma texture is studied and three detectors: One-step generalised likelihood ratio test (1S-GLRT), maximum a posteriori GLRT (MAP-GLRT) and two-step GLRT (2S-GLRT) are proposed. The detectors have the same structure with their test statistics and modified thresholds, respectively, related to the scale and the shape parameters of the texture, which can also be formulated in a matched filter (MF) form. Subsequently, the performance assessments are given by their probability of detection and probability of false alarm. The authors find that the probability of false alarm is dependent on the shape parameter, meaning the detectors have no CFAR property. When the shape parameter and the number of the integrated radar pulses satisfy certain condition, it has no relation with the shape parameter and then the detectors have CFAR property. Finally, simulation results show that: (i) 1S-GLRT and MAP-GLRT have the same performance for fixed probability of false alarm and 2S-GLRT bears slightly bad performance; (ii) the performance of 1S-GLRT is much closer to the adaptive coherence estimator (ACE) and is better than that of the Kelly GLRT and (iii) the 1S-GLRT is robust when parameter estimation errors exist. View full abstract»

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  • An adaptive filtering algorithm for blind waveform estimation in diffuse multipath channels

    Page(s): 322 - 330
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (651 KB)  

    The use of spatial filtering is considered to isolate a single propagation mode of an unknown narrowband signal received as a superposition of multipath components by a sensor array for the purpose of source waveform estimation. In the problem addressed, multipath propagation from source to receiver occur due to diffuse scattering from a number of distinct but extended regions of an irregular medium rather than ideal specular reflection. The combined presence of diffuse scattering and array calibration uncertainties may cause the spatial signatures of the incident distributed signal modes to deviate significantly from the plane-wave array manifold. Furthermore, the temporal signature of the waveform to be recovered may also be quite arbitrary, with no known deterministic or statistical properties that can be utilised for multipath separation. The lack of knowledge regarding the propagation channel, array manifold and source waveform poses a major challenge for the task at hand. This study proposes a new blind spatial filtering technique, referred to as the generalised estimation of multipath signals (GEMS) algorithm, which can effectively separate distributed signal modes for accurate source waveform estimation. This algorithm actually exploits the presence of multipath propagation and wavefront distortions as the basis for signal separation. The performance of GEMS is compared with two benchmark signal-copy procedures using real data from an experimental finite impulse response single-input multiple-output high frequency (HF) system. View full abstract»

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  • Performance of knowledge aided space time adaptive processing

    Page(s): 331 - 340
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (528 KB)  

    In this study, the asymptotic average signal-to-interference plus noise ratio (SINR) loss of knowledge-aided (KA) space time adaptive processing (STAP) is derived based on the random matrix theory. The authors observe that the desired steering vector and a priori covariance matrix is whitened by the covariance matrix of cell under test. An important result in this study is that one finds the SINR loss of KA STAP can be factorised into two parts. The first part of SINR loss is determined by the number of independent and identically distributed secondary samples, system degree of freedom, colour loading level and the eigenvalues of whitened a priori covariance matrix. The angle between two vectors accounts for the second part of SINR loss, where the first vector is the whitened desired steering vector, the second vector is a rotated version of this whitened vector with the rotation matrix equal to whitened a priori covariance matrix. Several cases including both accurate a priori knowledge and inaccurate a priori knowledge as the colour loading matrix are studied. Performance loss because of inaccurate a priori knowledge is analysed. Numerical simulations are conducted to validate the authors theoretical analysis, shows that the results based on random matrix theory fit the empirical results by Monte-Carlo trials well. View full abstract»

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  • Unambiguous doppler centroid estimation approach for synthetic aperture radar data based upon compressed signal magnitude

    Page(s): 341 - 348
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (625 KB)  

    A new approach to Doppler ambiguity resolution is presented. This approach adopts the fact that the absolute Doppler centroid is a linear function of range frequency. Based on this concept, an alternative azimuth compression method that is without a prior knowledge about the motion parameters is developed and carried out in range frequency domain to accumulate the target energy along the azimuth. The resulting trajectories become straight lines with the same slope proportional to the unwrapped Doppler centroid. This slope can be well estimated by the azimuth cell walk correction/integration method. Two sets of measured synthetic aperture radar data (airborne and spaceborne radar) show that this approach works well in medium- and high-contrast scenes. View full abstract»

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  • Exact analytical two-dimensional spectrum for bistatic synthetic aperture radar in tandem configuration

    Page(s): 349 - 360
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1020 KB)  

    An exact analytical solution for the two-dimensional (2-D) point target spectrum is usually difficult to obtain because of the existence of a double-square-root (DSR) term in the bistatic range equation. Some approximate solutions for the 2-D spectrum have been derived and used in order to focus bistatic synthetic aperture data. A geometry-based bistatic formula (GBF) method was used for obtaining a quasi-analytical form of a bistatic 2-D spectrum by Zhang (2007). Although the GBF method cannot completely solve the problem of the DSR term, it provides a novel aspect for dealing with this problem. In this study, based on the quasi-analytical spectrum, the authors change the signal expression space and transform the eight-order polynomial equation in terms of the slow time into the four-order polynomial equation in terms of the half quasi-bistatic angle (HQBA) for the tandem configuration. Then the DSR-term problem is successfully solved and a corresponding exact analytical bistatic 2-D spectrum is obtained. It is proved that the spectra acquired by Rocca's smile operator, Loffeld's bistatic formula (LBF) and the method of series reversion (MSR) are equivalent to this proposed analytical spectrum when certain conditions are met, and that this exact analytical spectrum is the most accurate among them. View full abstract»

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  • Sandglass transformation for synthetic aperture radar detection and imaging of ship at low signal-to-clutter-plus-noise ratio

    Page(s): 361 - 373
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (971 KB)  

    Space/air-borne synthetic aperture radar (SAR) detection and imaging of moving ships at sea are important for ocean reconnaissance and fishery monitoring. A novel algorithm based on sandglass transformation to detect weak ships and form high-quality images under the conditions of low signal-to-clutter-plus-noise ratio is presented here. It requires no prior information about motion parameters of targets. The sandglass transformation can decouple the time and lag time in the instantaneous autocorrelation function of a linear frequency modulated (LFM) signal. Thus the cross-range signals of ship in the approximate form of LFM signals can be integrated coherently via the two-dimensional fast Fourier transformation. The proposed algorithm can not only achieve high-energy accumulation gain, but also suppress the interference of cross terms effectively without loss of resolution. Hence, it is effective to detect weak ships and generate high-resolution images. Numerical and experimental results confirm the effectiveness of the proposed algorithm. View full abstract»

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  • New method for generating site-specific clutter map for land-based radar by using multimodal remote-sensing images and digital terrain data

    Page(s): 374 - 388
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1508 KB)  

    By using multimodal remote-sensing images and digital terrain data of the environment, this study presents a new method for generating the clutter map specific to the selected land radar site and the radar's operating parameters. In the proposed method, the estimation of backscattering from the environment involves extrapolation of the airborne radar remote-sensing image to provide the baseline values, classification of multispectral remote-sensing satellite images to provide a detailed description of terrain types, use of digital terrain elevation data with the land radar position and height to provide local grazing angles and a terrain visibility map and use of the digital topographic map to provide the geometric reference for all data sets. Using actual remote-sensing images and digital terrain data acquired from a real environment with various terrain features, the clutter map generated by the proposed method for land-based radar is compared with that generated by the competitive modelling method. The accuracy of the proposed method is demonstrated based on the differences with respect to the actual clutter measurements using a different airborne radar-sensing configuration. 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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