Showing papers in "Iet Radar Sonar and Navigation in 2016"
TL;DR: A novel phase-modulation based dual-function system with joint radar and communication platforms that allows information delivery to the intended communication receiver regardless of whether it is located in the sidelobe region or within the main radar beam.
Abstract: The authors develop a novel phase-modulation based dual-function system with joint radar and communication platforms. A bank of transmit beamforming weight vectors is designed such that they form the same transmit power radiation patterns, whereas the phase associated with each transmit beam towards the intended communication directions belongs to a certain phase constellation. During each radar pulse, a binary sequence is mapped into one point of the constellation which, in turn, is embedded into the radar emission by selecting the transmit weight vectors associated with that constellation point. The communication receiver detects the phase of the received signal and uses it to decode the embedded binary sequence. The proposed technique allows information delivery to the intended communication receiver regardless of whether it is located in the sidelobe region or within the main radar beam. Three signalling strategies are proposed which can be used to achieve coherent communications, non-coherent communications, and non-coherent broadcasting, respectively. It is verified that the proposed method provides improved bit error performance as compared to previously reported sidelobe modulation based dual-functionality techniques.
145 citations
TL;DR: What FDA is and why it could be exploited for radar and navigation applications from a top-level system description is introduced and appeal to the radar signal processing and system engineering communities for more investigations on this promising array technique.
Abstract: Different from phased array providing only angle-dependent transmit beampattern, frequency diverse array (FDA) employs a small frequency increment across its array elements to provide range-angle-dependent transmit beampattern. This enables the array beam to scan without the need of phase shifters or mechanical steering. Since FDA has received much attention in antenna and radar signal processing societies, it is necessary to make an overview on this interesting topic. This study introduces what FDA is and why it could be exploited for radar and navigation applications from a top-level system description and appeal to the radar signal processing and system engineering communities for more investigations on this promising array technique. The status of FDA studies is overviewed and the most recent advances of FDA radar are discussed. The basic FDA system architectures are introduced, along with performance compared to a conventional phased-array. Next, guidelines for choosing good system parameters and typical implementation schemes are provided. Finally, potential applications in range and angle estimation of targets, cognitive FDA radar and low probability of identification FDA radar are discussed, along with several technical challenges.
142 citations
TL;DR: In this paper, the problem of spectrum sensing and spectrum sharing for cognitive radar operating in spectrally dense environments is considered and an algorithm for estimating the channel parameters that characterise the behaviour of the primary user of the channel is presented.
Abstract: This study deals with the problem of spectrum sensing and spectrum sharing for cognitive radar operating in spectrally dense environments. The authors focus on how compressed sensing in spectrum sensing can allow a significant reduction in acquisition time reducing the cost for high-resolution analogue-to-digital converters. They derive an algorithm for estimating the channel parameters that characterise the behaviour of the primary user of the channel and also define a spectrum-sharing method to minimise the interference between the radar and the primary user.
58 citations
TL;DR: A common framework for inverse synthetic aperture radar (ISAR) imaging via CS is provided and a CS-based ISAR imaging method is proposed and the effectiveness of the proposed method is demonstrated on real datasets and the performance evaluated by means of image contrast.
Abstract: The applicability of compressive sensing (CS) to radar imaging has been recently proven and its capability to construct reliable radar images from a limited set of measurements demonstrated. In this study, a common framework for inverse synthetic aperture radar (ISAR) imaging via CS is provided and a CS-based ISAR imaging method is proposed. The proposed method is tested for application such as image reconstruction from compressed data, resolution enhancement and image reconstruction from gapped data. The effectiveness of the proposed method is demonstrated on real datasets and the performance evaluated by means of image contrast.
52 citations
TL;DR: The authors present a coherent integration architecture for PBR, which consists of a frequency-domain pulse compression module to reduce the overall runtime for the computation of the cross-ambiguity function, and an efficient decimated keystone transform module based on the chirp z-transform to compensate the range migration.
Abstract: In this study, the problem of efficient implementation of a coherent integration processor in passive bistatic radars (PBRs) in the presence of range migration is addressed. The authors present a coherent integration architecture for PBR, which consists of a frequency-domain pulse compression module to reduce the overall runtime for the computation of the cross-ambiguity function, and an efficient decimated keystone transform module based on the chirp z-transform to compensate the range migration. The proposed architecture is then implemented in a hybrid central processing unit plus graphic processing unit scheme. Real measurement data are used to verify the superior integration performance and reduced computational complexity achieved by the proposed scheme.
51 citations
TL;DR: In this article, a method based on keystone transform, fold factor phase term compensation and generalised dechirp process is proposed to remove the migrations (RM and DFM) and realize the coherent accumulation.
Abstract: Coherent integration for high-speed multi-targets detection is a challenging task in radar applications. First, range migration (RM) and Doppler frequency migration (DFM) induced by target's complex motions (i.e. high speed, acceleration, etc.) would result in serious integration performance loss. Second, if the scattering intensities of different targets differ significantly, the weak one would be shadowed by the strong target and makes it difficult to achieve the coherent accumulation for weak target. Existing methods either perform poorly or are too computationally expensive for coherent integration of high-speed manoeuvring targets. Two contributions are made towards addressing these limitations. First, a method based on keystone transform, fold factor phase term compensation and generalised dechirp process is proposed to remove the migrations (RM and DFM) and realise the coherent accumulation. Compared with the generalised Radon Fourier transform algorithm, the proposed method can avoid the blind speed sidelobe and has a much lower computational cost. Second, two CLEAN techniques based on sinc-like point spread function (PSF) and modified PSF are presented to eliminate the strong target's effect and highlight the weak ones. By this way, the coherent integration of strong target and weak ones can be achieved iteratively. Several simulations are provided to demonstrate the effectiveness.
49 citations
TL;DR: In this paper, a quasi-real-time human respiration detection method with prominent signal-to-noise-and-clutter ratio (SNCR) improvement is proposed to increase performance of ultra-wideband rescue radar under the low SNCR conditions such as through-wall or other similar conditions.
Abstract: In this study, a quasi-real-time human respiration detection method with prominent signal-to-noise-and-clutter ratio (SNCR) improvement is proposed to increase performance of ultra-wideband rescue radar under the low SNCR conditions such as through-wall or other similar conditions. Three main steps of the proposed method are designed for the purpose of effectively removing stationary clutter, suppressing non-stationary interference from other moving subject and improving the contrast between respiration response and clutter. Meanwhile, the proposed method satisfies the requirement of quasi-real time as its time cost implemented in MATLAB is only 2 s. Experiments are carried out in through-wall/floors/artificial-ruin conditions, and results show that the proposed method outperforms the previously proposed method, and it can be a good choice for human respiration detection in complex scenarios due to the prominent SNCR improvement.
48 citations
TL;DR: In this article, the authors investigated the relationship between mean Doppler shift and local spectrum intensity and found that when looking up or down wind, there is a strong correlation between mean DOF shift and spectrum intensity, which can be combined with random fluctuations of spectrum width to give the spectra a temporal and spatial variability.
Abstract: This study is concerned with the characterisation of Doppler spectra from high range resolution X-band radar sea clutter observed from an airborne platform over the range of grazing angles, 15° to 45°. It is observed that when looking up or down wind there is a strong correlation between mean Doppler shift and local spectrum intensity. When combined with random fluctuations of spectrum width, these characteristics give the spectra a temporal and spatial variability. This behaviour has previously been observed in low grazing angle data and these results confirm the wider applicability of the models developed using that data. The modelling method is also extended here to capture the bimodal behaviour observed with high intensity returns from breaking waves looking up or down-wind.
48 citations
TL;DR: In this paper, an efficient coherent integration method based on keystone transform (KT) and Lv's distribution (LVD) is proposed to detect a moving target in low-noise ratio environment.
Abstract: This study considers the coherent integration problem for detecting a manoeuvring target, involving range migration (RM) and Doppler frequency migration (DFM) within the coherent processing interval. An efficient coherent integration method based on keystone transform (KT) and Lv's distribution (LVD) is proposed. It can not only correct the RM effect by KT and fold factor phase compensation, but also remove the DFM effect and achieve the coherent accumulation via LVD. Compared with the moving target detection, Radon-Fourier transform, and Radon-fractional Fourier transform algorithms, the proposed method can obtain better detection ability under low signal-to-noise ratio environment. Finally, several simulations are provided to demonstrate the effectiveness.
47 citations
TL;DR: The authors propose a novel thinned STAP through selecting an optimum subset of antenna-pulse pairs that achieves the maximum output signal-to-clutter-plus-noise ratio and utilises a new parameter, named spatial spectrum correlation coefficient, to analyze the effect of space-time configuration on STAP performance and reduce the dimensionality of traditional STAP.
Abstract: The authors address the problem of slow target detection in heterogeneous clutter through dimensionality reduction. Traditional approaches of implementing the space-time adaptive processing (STAP) require a large number of training data to estimate the clutter covariance matrix. To address the issue of limited training data especially in the heterogeneous scenarios, they propose a novel thinned STAP through selecting an optimum subset of antenna-pulse pairs that achieves the maximum output signal-to-clutter-plus-noise ratio. The proposed strategy utilises a new parameter, named spatial spectrum correlation coefficient, to analytically characterise the effect of space-time configuration on STAP performance and reduce the dimensionality of traditional STAP. Two algorithms are proposed to solve the antenna-pulse selection problem. The effectiveness of the proposed strategy is confirmed by extensive simulation results, especially by utilising the multi-channel airborne radar measurement data set.
47 citations
TL;DR: In this paper, an enhanced short-time Fourier transform (STFT)-based jamming mitigation system which employs several windows to increase time-frequency (t-f) plane resolution is proposed.
Abstract: In this study, an enhanced short-time Fourier transform (STFT)-based jamming mitigation system which employs several windows to increase time–frequency (t–f) plane resolution is proposed. A technique for employing near-optimum windows is also proposed. It is observed that selection of these windows leads to increasing the resolution of the t–f representation. An infinite impulse-response notch filter is employed for jamming removal process. Performance of the proposed method is evaluated by a set of measured global positioning system data. It is compared with conventional STFT-based algorithms reported in literature.
TL;DR: A novel stable dictionary learning method is proposed that relies on the constraints that the sparse representations of adjacent HRRPs without scatterers' motion through range cells should have the same support and lower variance and automatically select the optimal dictionary basis vectors for stable sparse coding.
Abstract: Sparse representation models based on dictionary learning have led to interesting results in signal restoration and target recognition. However, due to the redundancy defined by overcomplete dictionary atoms in new space, finding sparse representations from inaccurate measurements may cause uncertainty and ambiguity. Especially for radar automatic target recognition using high-resolution range profiles (HRRP), the target-aspect sensitivity, amplitude fluctuation and outliers in HRRPs could result in mismatch among the sparse representations of the same class and thus deteriorate the recognition performance. This article proposes a novel stable dictionary learning method to deal with this problem and improve the pattern recognition performance. The proposed method relies on the constraints that the sparse representations of adjacent HRRPs without scatterers' motion through range cells should have the same support and lower variance. The structured sparse regularisation is then used to automatically select the optimal dictionary basis vectors for stable sparse coding. Experiments based on the measured HRRP dataset validate the performance of the proposed method. Moreover, encouraging results are reported with small training data size and under different signal-to-noise ratio conditions.
TL;DR: In this paper, a weighted least squares method is proposed to determine the position of an individual target in the presence of multiple transmitters and multiple receivers from time difference of arrival measurements.
Abstract: This study proposes a weighted least squares method to determine the position of an individual target in the presence of multiple transmitters and multiple receivers from time difference of arrival measurements. The method is based on the intersection of the ellipsoids defined by bistatic range measurements from a number of transmitters and receivers. The solution is derived from the minimisation of the weighted equation error energy. In addition, the method requires no initial guess of the solution to find the target location. A weighting matrix is obtained in two different conditions in order to generate a substantial improvement in the performance of the method, which one of them leads to an approximate maximum-likelihood estimator and the other one results in a best linear unbiased estimator. A detailed theoretical error analysis associated with this method is presented and the Cramer-Rao lower bound is also derived. Simulations are included to examine the algorithm's performance and corroborate the theoretical developments.
TL;DR: In this paper, the authors proposed a cognitive FDA radar with a range-angle-dependent beampattern, which can adaptively change its frequency increment according to the environment and thus better performance can be obtained.
Abstract: By jointly utilising the advantages of cognitive radar with situational awareness due to closed-loop control and frequency diverse array (FDA) with range-angle-dependent beampattern, this study proposes a cognitive FDA radar with situational awareness. Different from conventional phased-array, FDA offers a range-dependent beampattern. The proposed cognitive FDA radar can avoid undesired strong interferences and focus to the desired targets through the presented closed-loop control algorithm. This algorithm aims to maximise the receiver output signal-to-interference-plus-noise ratio (SINR) performance by iteratively optimising the frequency increment in a closed-loop manner. That is, the cognitive FDA radar can adaptively change its frequency increment according to the environment and thus better performance can be obtained. The cognitive FDA radar performance is evaluated by examining the SINR and direction-of-arrival (DOA) estimation mean square errors. How the performance depends on the FDA frequency increment is also investigated. Simulation results show that the cognitive FDA radar yields much better SINR performance and thus higher DOA estimation precision than basic FDA and conventional phased-array radars.
TL;DR: It is shown that classification accuracy above 95% can be achieved using a single feature and features based on singular value decomposition and on the centroid of the micro-Doppler signature are proposed and their suitability for armed versus unarmed classification purposes discussed.
Abstract: This study analyses the use of human micro-Doppler signatures collected using a multistatic radar system to identify and classify unarmed and potentially armed personnel walking within a surveillance area. The signatures were recorded in a series of experimental tests and analysed through short time Fourier transform followed by feature extraction and classification. Features based on singular value decomposition and on the centroid of the micro-Doppler signature are proposed and their suitability for armed versus unarmed classification purposes discussed. It is shown that classification accuracy above 95% can be achieved using a single feature. Features based on the centroid of the signatures are shown to be also effective in cases where there are two people walking together in the same direction and at similar speed, and one of them may be armed or not, i.e. for targets not easily separable in range or in Doppler.
TL;DR: This study approaches the problem of separating humans from indoor targets through machine learning techniques by implementing support vector machine (SVM) classifiers by implementing finite-difference time-domain (FDTD) method.
Abstract: Through-the-wall radar systems are typically plagued by harsh clutter which confounds the detection and classification of targets. This study approaches the problem of separating humans from indoor targets through machine learning techniques by implementing support vector machine (SVM) classifiers. Simulated and experimental data are used to evaluate the suitability of SVMs for target classification via their spectral characteristics. Numerical modelling of humans and indoor clutter was accomplished through the finite-difference time-domain (FDTD) method. The radar cross-sections for the various objects are acquired over a wide range of frequencies, polarisations, aspect angles, and material properties. Furthermore, the spectral properties of humans and clutter targets are measured using a network analyser. The potentials of the acquired simulated and experimental spectral characteristics at different frequencies and polarisations are explored for target classification using SVMs. Feature selection algorithms are also investigated to reduce the redundancy and model complexity. Finally, the classification performance is assessed in the presence of additive white Gaussian noise and through various wall materials.
TL;DR: A new ghost elimination method that removes multipath echoes from the raw radar data is proposed that can preserve the true targets while eliminating the ghosts even if the targets overlap with those ghosts.
Abstract: In through-wall radar imaging, the multipath echoes caused by specular reflections at interior walls of an enclosed room will lead to multipath ghosts in the resulting image. The ghosts appear like the true targets and therefore tend to increase the number of false alarms. To solve this problem, a new ghost elimination method that removes multipath echoes from the raw radar data is proposed in this study. With a priori knowledge of the room, a concise multipath model is first developed, based on which the locations of the multipath echoes can be determined. Then, a cancellation process that consists of two steps is performed wherein the multipath echoes are cancelled in a specific order depending on the positions of the targets they correspond to. The major advantage of this method is that it can preserve the true targets while eliminating the ghosts even if the targets overlap with those ghosts. The effectiveness of the proposed method is validated by the processed imaging results using both the finite-difference time-domain-simulated data and the real experimental data.
TL;DR: Results show that the LTE-based passive radar can detect and track the ground vehicle at different locations, speeds and trajectories, and localise it in the XY-axis coordinate.
Abstract: This study examines the feasibility of the recently deployed wireless communication system, namely, long-term evolution (LTE), for passive radar applications. Specifically, the capability of the system to detect and track a ground moving target is analysed. A theoretical analysis is conducted on the actual LTE signal transmitted in the atmosphere, followed by field experimentation using a moving vehicle with different bistatic geometries. The experiment examines the capability of an LTE-based passive radar to detect a moving vehicle and then track it using a standard Kalman filter. Results show that the LTE-based passive radar can detect and track the ground vehicle at different locations, speeds and trajectories, and localise it in the XY-axis coordinate.
TL;DR: The main property of the hybrid codes is the capability of digital beamforming on transmit just like with a set of orthogonal signals employed by coherent multiple-input–multiple-output radar and simplicity (only one waveform has to be generated in time).
Abstract: This study presents a simple yet ingenious transmit diversity technique (so-called hybrid codes) for phased array radar. Its main property is the capability of digital beamforming on transmit just like with a set of orthogonal signals employed by coherent multiple-input–multiple-output radar and simplicity (only one waveform has to be generated in time). The performance of the hybrid codes is examined by analysing the transmit ambiguity functions containing beampatterns and range profile for all angular directions of interest.
TL;DR: In this article, a new signal fusion-based method for discriminating active false targets from desired real targets is proposed based on Neyman-Pearson lemma, which can discriminate false targets generated by deception signals with arbitrary modulation.
Abstract: The anti-jamming methods available in multistatic radar are mostly based on data fusion processing and therefore do not fully explore its anti-jamming ability. In the view of multistatic radar, the echoes of real targets received by the widely separated receivers would be independent from each other due to the independence of target radar cross sections in different scattering directions. However, the deception jamming received by the same receivers would be highly correlated since the jamming signals transmitted to different directions are identical. Therefore, real targets would differ from false targets in the spatial scattering property in multistatic radar. By exploiting this phenomenon, a new signal fusion-based method for discriminating active false targets from desired real targets is proposed in this study based on Neyman–Pearson lemma. In this method, false targets are identified by correlation test between the complex envelopes of arbitrary two targets in different receivers. The new method can discriminate false targets generated by deception signals with arbitrary modulation. The closed-form expression for the rejection probability of false targets is derived. Both theoretical analysis and simulations verify the feasibility of the proposed method.
TL;DR: A study carried out in north-eastern Poland on the role of ionospheric delays in the integrity model according to the Radio Technical Commission for Aeronautics guidelines found that the first method is characterised by only slightly better accuracy results, while significant differences were obtained by examining the integrity of positioning.
Abstract: Integrity of positioning is one of the key aspects of satellite based augmentation systems. This paper presents a study carried out in north-eastern Poland, a region which is considered as a border of the operation of the European Geostationary Navigation Overlay Service (EGNOS) system. Detailed analyses concerning operational parameters of EGNOS were done during the 12-hour and 24-hour measurement sessions conducted at a fixed point. The study was focused on the role of ionospheric delays in the integrity model according to the Radio Technical Commission for Aeronautics guidelines. In determination of the accuracy and integrity of positioning, two variants of calculations were adopted: one based on a standard interpolation algorithm determining ionospheric delay by the EGNOS system, and the other based on the Klobuchar model. The research found that the first method is characterised by only slightly better accuracy results, while significant differences were obtained by examining the integrity of positioning. For both variants of the calculation design, the values of protection levels determined for the fixed point are much higher than the positioning accuracy, which meets the integrity requirements of the navigation system.
TL;DR: The periodic waveform's high-average duty cycle makes it a ‘quasi continuous wave (CW) non-coherent waveform’, which avoids the pulse–train conflict between average power and unambiguous range.
Abstract: The growing interest in adopting pulse compression waveforms to non-coherent radar and radar-like systems (e.g. lidar) invites this update and review. The authors present different approaches of designing on–off {1, 0} coded envelopes of transmitted waveforms whose returns can be envelope detected and non-coherently processed. Two approaches are discussed for the aperiodic case: (a) Manchester encoding and (b) mismatched reference. For the periodic case, on–off sequences are described, which produce perfect periodic cross-correlation when cross-correlated with one or more integer number of periods of a two-valued reference sequence {1, −b}. This study provides comprehensive rules for designing periodic on–off waveforms and their references. The periodic waveform's high-average duty cycle (over 50%) makes it a ‘quasi continuous wave (CW) non-coherent waveform’, which avoids the pulse–train conflict between average power and unambiguous range. Good experimental results with a laser range finder are presented. Reports on other uses are quoted.
TL;DR: In this paper, a Kalman filtering-based method was proposed to exploit the temporal correlation of target scattering coefficients (TSCs) and improve the corresponding estimation performance, where an additional weight vector was introduced to achieve a tradeoff among different targets.
Abstract: In cognitive radar systems, a closed-loop feedback is formed by the transmitter, environment, and receiver. Then, the transmit waveform can be optimised to improve the radar estimation performance. Unlike existing works that only consider single target with temporally correlated characteristic, waveform design for multiple extended targets is investigated in this study. The authors propose a Kalman filtering (KF)-based method to exploit the temporal correlation of target scattering coefficients (TSCs) and improve the corresponding estimation performance. Additionally, for the targets of both closed and separated in range, a novel optimisation problem is established to design the transmit waveform and minimise the mean square error of estimated TSC at each KF iteration, where an additional weight vector is introduced to achieve a trade-off among different targets. Since the optimisation problem is non-convex and cannot be solved efficiently, a two-step method is proposed to convert it into a convex problem, which can be solved by an optimisation toolbox such as CVX. Simulation results demonstrate that the joint method of waveform design outperforms the existing methods in TSC estimation for both separated and closed targets, and offers much more flexibility.
TL;DR: The wideband full coherence technology based on stepped frequency signal is proposed to improve system robustness to time synchronisation error, which makes the DCAR technology more realisable in engineering.
Abstract: As the next generation radar, although the distributed coherent aperture radar (DCAR) has been proposed and some basic works have been developed in recent years, this new radar technology has not been researched systematically. In this study, the concept and closed-loop workflow of DCAR are described in detail first. Then, the coherent parameters (CPs), which play an important role to realise full coherence in DCAR, are estimated based on orthogonal signal and coherent signal. To investigate the limits of estimation accuracy of CPs, the Cramer–Rao lower bounds are derived. The estimation values of CPs are filtered using Kalman filter to improve the estimation accuracy. In the following, the wideband full coherence technology based on stepped frequency signal is proposed to improve system robustness to time synchronisation error, which makes the DCAR technology more realisable in engineering. Furthermore, a grating lobe suppression method based on modified genetic algorithm in synthetic array pattern of DCAR is presented. Ultimately, the experiments are carried out using test system to verify the theory of wideband DCAR.
TL;DR: In this article, the matched-filter properties of an LFM radar signal modulated by a phase-switched screen (PSS) have been investigated and it has been shown that even though the radar receiver bandwidth has been corrupted to aliasing by component of the reflected signal, the PSS is shown to be equally effective in shielding a target and additionally provide a multiple-decoy capability.
Abstract: The phase-switched screen (PSS) imposes phase modulation onto the radar-reflected signal so that its energy is redistributed into sidebands that lie outside the receiver pass-band. However, when illuminated by a wideband linear frequency modulation (LFM) radar, the modulated reflected signal may still occupy the radar pass-band if the LFM signal bandwidth is greater than the modulating frequency. Previous research about the reflectivity performance of a PSS against LFM radar illumination focuses mainly on the frequency spectrum characteristics. In this study, an investigation has been carried out to determine the matched-filter properties of an LFM radar signal modulated by a PSS. Theoretical analyses and simulation results have proven that even though the radar receiver bandwidth has been corrupted to aliasing by component of the reflected signal, the PSS is shown to be equally effective in shielding a target and additionally provide a multiple-decoy capability.
TL;DR: Tracking and navigation results show that the federated UTC GPS/INS integrated system based on VT improves both the tracking and navigation performance significantly under severe jamming environments compared with that of ST system.
Abstract: Considering all integration methods currently available for global positioning system (GPS) and inertial navigation system (INS) integrated navigation system, ultra-tightly coupled (UTC) GPS/INS system is the best choice for accurate and robust navigation. However the performance of UTC GPS/INS system based on scalar tracking (ST) degrades in severe jamming environments. To solve this problem an innovative federated UTC GPS/INS system based on vector tracking (VT) is proposed. On the basis of UTC integration, three Kalman filters are developed to accomplish the goals of signal amplitude estimation, VT and integration navigation. By replacing the traditional ST loops with VT filter, the tracking ability is remarkably reinforced. More importantly, a new mathematical model of VT is proposed and the key innovation of this model is that it can provide adaptation ability to integration Kalman filter, so that the navigation performance can be improved under various jamming conditions. A simulation platform covering all procedures of GPS/INS integrated navigation is employed to verify the effectiveness of the proposed architecture. Tracking and navigation results show that the federated UTC GPS/INS integrated system based on VT improves both the tracking and navigation performance significantly under severe jamming environments compared with that of ST system.
TL;DR: Numerical study results show that the expanded CBMeMBer filter in the proposedSMC implementation can dramatically improve estimation accuracy in comparison with general SMC implementation and gives a more accurate estimation than original CBMe MBer filter while performs more time-efficiently than PHD filter for extended target tracking.
Abstract: It has been shown that the cardinality balanced multi-target multi-Bernoulli (CBMeMBer) filter can extract multi-target states efficiently and reliably. However, when faced with extended targets, it will lead to overestimation. Therefore, a CBMeMBer filter for extended targets tracking is proposed in this study. Three main contributions are made in this study: first, analytical recursion equations of the proposed CBMeMBer filter are derived and relevant proofs are presented. Second, a novel sequential Monte Carlo (SMC) implementation is proposed, which approximates the sample point using several σ points rather than state transition function. Third, to reduce the particle weight degeneracy problem, a new resample method is introduced. Finally, comparisons between the CBMeMBer and probability hypothesis density (PHD) filters for extended targets tracking are studied through a non-linear example. Numerical study results show that the expanded CBMeMBer filter in the proposed SMC implementation can dramatically improve estimation accuracy in comparison with general SMC implementation. Meanwhile, the authors also find that the proposed CBMeMBer filter gives a more accurate estimation than original CBMeMBer filter while performs more time-efficiently than PHD filter for extended target tracking.
TL;DR: An algorithm for three-dimensional (3D) target reconstruction based on the use of 2D inverse synthetic aperture radar (ISAR) imaging and interferometry is proposed, able to operate with both bistatic and squinted geometry, thus allowing its applicability to all possible geometrical configurations.
Abstract: An algorithm for three-dimensional (3D) target reconstruction is proposed in this study. Such an algorithm is based on the use of 2D inverse synthetic aperture radar (ISAR) imaging and interferometry. The proposed algorithm is able to operate with both bistatic and squinted geometry, thus allowing its applicability to all possible geometrical configurations. A mathematical foundation of the algorithm is provided in this study followed by a validation through the use of both simulated and real data.
TL;DR: In this article, the authors proposed a new broadband target detection algorithm for FM-based passive bistatic radar systems, which simultaneously exploits multiple FM radio channels transmitted by the same transmitting station.
Abstract: In this study, the authors propose a new broadband target detection algorithm for FM-based passive bistatic radar systems, which simultaneously exploits multiple FM radio channels transmitted by the same transmitting station. It is shown that the joint exploitation of the signals of opportunity received at multiple carrier frequencies improves target detection capability as well as the target range resolution. In addition, the proposed detection algorithm exploits all available information making the detection performance robust against time-varying program content broadcast by the individual FM radio channels. Therefore, after formulating the broadband target detection problem as a composite hypothesis test, they derive a broadband uniformly most powerful invariant (B-UMPI) test, together with a closed-form expression for a statistical threshold that allows for automatic detection. To get a better insight into the detection performance of the proposed detector, a close-form expression for the probability of detection is also derived. In addition, they analytically show that how the range resolution of the proposed broadband target detection algorithm improves. They also analytically obtain an integrated sidelobe level ratio at the output of the B-UMPI statistics to show an improvement in the target detection quality. Finally, they provide some simulation examples to validate the authors’ theoretical analysis as well as to show the improvement in the target detection capability and the target range resolution in the broadband FM-based passive bistatic radar systems.
TL;DR: In this paper, an improved m-D jamming method based on phase-switched screen (PSS) is proposed, which combines the advantage induced by the PSS modulation and the usefulness of the m-d jamming.
Abstract: Target micro-motions such as rotation and vibration introduce phase modulation, termed as micro-Doppler (m-D) effect, onto synthetic aperture radar (SAR) signals. This causes ghost targets in the reconstructed SAR images. Inspired by this unique characteristic, a passive-jamming method based on m-D was developed for SAR. The m-D jamming method utilised a rotating reflector to intentionally generate ghost targets as jamming strips on the SAR image so as to protect certain areas. The m-D jamming method based on a single rotating reflector can only generate a long jamming strip along the azimuth direction but located in a finite number of range cells, which restricts the region of protected scene. In this study, an improved m-D jamming method based on phase-switched screen (PSS) is proposed, which combines the advantage induced by the PSS modulation and the usefulness of the m-D jamming. By controlling the modulating frequency and waveform of the PSS, the jamming strip is enlarged along the range direction. Theoretical analyses and simulation results verify the validity of the proposed method.