IET Radar, Sonar & Navigation
Print ISSN
1751-8784
Online ISSN 1751-8792
Online ISSN 1751-8792
IET Radar, Sonar & Navigation covers the theory and practice of systems involving the processing of signals for radar, radiolocation, radionavigation and surveillance purposes.
Examples of the fields of application include:
radar, sonar, electronic warfare, avionic and navigation systems. Processing directed towards the above application areas includes advances in waveform design, adaptive array and superresolution methods, tracking algorithms, synthetic aperture, and target recognition techniques.
This publication was previously known as IEE Proceedings - Radar, Sonar and Navigation 1994-2006. ISSN 1350-2395. more..
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Editorial: RSN Editorial 2013
- Author(s): Hugh Griffiths
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1
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Design of artificial landmarks for underwater simultaneous localisation and mapping
- Author(s): Yan Pailhas; Chris Capus; Keith Brown; Yvan Petillot
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p.
10
–18
(9)
The use of autonomous underwater vehicles for a variety of purposes is set to increase in the future. A key issue is accurate navigation, especially for survey applications large cumulative error are introduced by the various position sensors: accelerometer; Doppler velocity log; compass; inertial navigation sensors. Algorithms such as simultaneous localisation and mapping rely on accurate landmark recognition in order to correct the vehicle position. This study proposes a solution based on broadband sonar and passive artificial coded landmarks to improve the navigation. Through resolution of the wave equation for acoustic propagation in a multilayer concentric sphere, it is shown that there is a great diversity in the echo spectrum with only small changes in internal structure. This enables the design of a set of passive landmarks, which can be identified unambiguously, since each has a characteristic signature or spectral code when insonified with a broadband sonar.
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Global Navigation Satellite System ambiguity decorrelation through diagonal elements precomputing and ordering method
- Author(s): Yao Yanxin; Ding Fan
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p.
19
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Integer ambiguity decorrelation has long been an important problem for global navigation satellite system high-precision relative positioning applications for its effect of deducing search number of candidate integer ambiguities. It is difficult to design a decorrelation method with fine performance. Among those decorrelation methods based on LDLT decomposition, direct-ordering method (DOM) is the one that follows the principle of ordering diagonal elements of variance–covariance matrix before decorrelation. In the present study, the authors propose a diagonal element precomputing and an ordering method (DEPOM) based on LDLT. DEPOM orders diagonal elements of the matrix according to values after LDLT decomposition, in contrast to DOM according to values before LDLT decomposition. Thus, DEPOM is closer to the aim of arranging the larger diagonal element to the larger row before decomposition. The nodus is to determine elements in decomposed L and D matrices, which constitutes an improved LDLT decomposition method. The above study show that DEPOM has better decorrelation degree and a higher success rate than DOM from the numerical simulation tests. The performance of DEPOM is equivalent to the united ambiguity decorrelation method. However, it is different. DEPOM is a supplement to the integer least-squares theory. The improved LDLT decomposition is also a new form in the LDLT decomposition family.
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Desensitised Kalman filtering
- Author(s): Christopher D. Karlgaard; Haijun Shen
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p.
2
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This study discusses the development of a desensitised optimal filtering technique for systems subject to plant and measurement model parameter uncertainties. Desensitised state estimates are obtained by minimising a cost function consisting of the posterior covariance matrix trace penalised by a weighted norm of the state estimate error sensitivities. The resulting filter is non-minimum variance but exhibits reduced sensitivity to deviations in the assumed plant model parameters. Solutions are obtained for discrete, continuous and mixed continuous-discrete non-linear systems using an extended Kalman filter formulation. An example problem involving orbit determination with parameter uncertainty is provided to illustrate the effectiveness of the proposed filtering technique.
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Bernoulli filter for joint detection and tracking of an extended object in clutter
- Author(s): Branko Ristic; Jamie Sherrah
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p.
26
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The problem is joint detection and tracking of a non-point or extended moving object, characterised by multiple feature points, which can result in detections. Owing to imperfect detection, only some of the feature points are detected and in addition, false alarms [or clutter] can also be present. Standard tracking techniques assume point objects, that is at most one detection per object, and hence are not adequate for this problem. This study presents a principled theoretical solution in the form of the Bayes filter, referred to as the Bernoulli filter for an extended object. The derivation follows the random set filtering framework introduced by Mahler. The filter is implemented approximately as a particle filter and subsequently applied both to simulated data and a real video sequence.
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Improved detection probability of a radar target in the presence of multipath with prior knowledge of the environment
- Author(s): Harun Taha Hayvaci; Antonio De Maio; Danilo Erricolo
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p.
36
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(11)
A new method to address radar target detection problems in multipath environments is considered. The novelty of the proposed method is that it exploits prior knowledge on the environment and combines it with ray-tracing electromagnetic modelling to determine some information about the possible multipath structure. This information is used to separate the environment into different regions based upon the behaviour of the multipath components. Specifically, as a case study, the authors consider a radar and a target in the presence of a perfectly reflecting planar surface. For this environment, three regions are determined based on the amount of overlap among the multipath components. For each region, receivers are designed exploiting the multipath structure. Thus, a different viewpoint to analyse radar detection problems is suggested. The two main results are the improvement in the target probability of detection, by properly accounting for the multipath and a priori determination of the best performing detector based upon the location of the target and the available signal-to-noise ratio.
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Robust non-homogeneity detection algorithm based on prolate spheroidal wave functions for space-time adaptive processing
- Author(s): Xiaopeng Yang; Yongxu Liu; Teng Long
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p.
47
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The estimated clutter covariance matrix is always corrupted by the interference target signals (outliers) in non-homogeneous clutter environments, which leads the performance of space-time adaptive processing (STAP) to be degraded significantly for clutter suppression. Therefore a robust non-homogeneity detection algorithm by utilising the prolate spheroidal wave functions (PSWF) is proposed to eliminate the outliers from the training samples set in this study, which can estimate the clutter covariance matrix more accurately for STAP. In the proposed method, the basis vectors of PSWF according to the system parameters are first calculated, which can be computed offline and stored in memory beforehand, and then the corresponding clutter covariance matrix is constructed. In the following, the constructed covariance matrix is combined with the generalised inner products (GIP) method to obtain the corresponding statistics. The training samples contaminated by the outliers are eliminated based on the comparison of the statistics and the designated threshold. By analysing the sensitive coefficients and the simulation results, it is found that the proposed method (PSWF-GIP) can more effectively eliminate the outliers and improve the performance of STAP in non-homogeneous clutter environments.
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Interference and multipath mitigation utilising a two-stage beamformer for global navigation satellite systems applications
- Author(s): Saeed Daneshmand; Ali Broumandan; John Nielsen; Gérard Lachapelle
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p.
55
–66
(12)
The performance of location-based services provided by global navigation satellite systems is compromised by interference and multipath propagations. Although time/frequency interference suppression methods have been widely studied in the literature, they fail to cope with wideband interference signals. Instead, techniques utilising several antenna elements can be employed to mitigate both narrowband and broadband interference signals. However, the performance of beamforming techniques utilising antenna arrays severely degrades in dealing with correlated and coherent multipath components which cause signal cancellation phenomenon and temporal correlation matrix rank deficiency. This study proposes a two-stage beamformer to jointly deal with interference and multipath signals. In the first stage, before the despreading process, by applying the subspace method, the interference subspace is estimated and used as a constraint for the optimisation problem in the next stage. In the second stage, a modified version of the minimum power distortionless response beamformer employing several overlapping sub-arrays called the minimum difference output power method is utilised to mitigate the correlated multipath components. The proposed beamformer can deal with the signal cancellation phenomenon and temporal correlation matrix rank deficiency. Several simulation examples and a real data test are provided to illustrate the effectiveness of the proposed beamformer. Results show that the proposed method is able to put deep nulls in the direction of the narrowband and wideband interference signals, and significantly reduces the multipath-induced time of the arrival error.
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Approach for near-real-time prediction of ionospheric delay using Klobuchar-like coefficients for Indian region
- Author(s): Ashish Kumar Shukla; Saurabh Das; Atul P. Shukla; Vilas S. Palsule
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p.
67
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Currently, global positioning system (GPS) satellites transmit the Klobuchar coefficients to estimate ionospheric delay for the single-frequency users. These coefficients are broadcast to the users on the basis of seasonal ionospheric variations and average solar flux. In low-latitude Indian region, prediction of the delay using these coefficient is not accurate because of complex behaviour of the ionospheric. In this study, new Klobuchar-like cofficients are generated using regional total electron content data collected from the 18 stations in Indian. Using these coefficients, a novel approach for near-real-time prediction of the ionospheric delay (for every 5 min) is proposed. This approach provides the opportunity to generate the Klobuchar-like coefficients using shorter data sets (1 day) rather than using long-term statistics of several years, as done in the generation of GPS broadcast Klobuchar coefficients. Performance of the prediction is evaluated for the geomagnetic quiet (Ap index <50) and severely disturbed (Ap index >300) days of 2005 and 2007. Prediction accuracy is significantly improved using the single-frequency users of the Regional Navigational Satellite Systems, such as the proposed Indian Regional Navigation Satellite System.
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Online low-sidelobe waveform generator for noise radars based on the graph theory
- Author(s): Hamed Haghshenas; Mohammad M. Nayebi
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p.
75
–86
(12)
A common and well-known method of signal processing in noise radars is measuring the cross-correlation between transmitted and received signals. However, it creates a lot of undesirable sidelobes which can mask weak echoes of far targets. There are many methods of masking effect removal based on signal processing at the receiver side. In this study, a method of waveform generation based on the graph theory is presented and its ability to reduce masking effect will be compared with that of radars using purely random waveforms. The method tries to design a graph consisting of nodes each corresponds to a random subsequence. After generating the graph offline, output sequence is produced online by moving from one node to another based on the probability of each edge. The subsequences are designed in a way that the correlation sidelobe levels generated by two subsequences of two connected nodes are reduced. In addition, a combination of the graph-based method and random step frequency modulation is presented to guarantee randomness of the resultant waveforms. The waveform randomness is measured and compared with purely random waveforms. It is shown, by means of extensive computer simulations, the proposed waveforms can produce smaller correlation sidelobes, while preserving randomness characteristics.
