This study presents a novel method for time–frequency (TF) signal analysis and chirp rate estimation dedicated for electromagnetic spectrum sensing, electronic warfare, electronic intelligence and/or passive bistatic radar purposes in which frequency modulated signals occur. The approach is based on the double-adaptive chirplet transform, providing optimal analysis window parameters, which is a crucial

The authors deal with the problem of detecting point-like targets in the presence of diffuse multipath under the assumption of a partially homogeneous Gaussian disturbance by introducing an unknown scaling factor which represents the mismatch between the noise contribution of the cell under test and the training samples. Also, they model the target echo as a superposition of direct plus multipath components

For high-resolution scene mapping and object recognition, optical technologies such as cameras and LiDAR are the sensors of choice. However, for future vehicle autonomy and driver assistance in adverse weather conditions, improvements in automotive radar technology and the development of algorithms and machine learning for robust mapping and recognition are essential. In this study, the authors describe

Drifting of anchor nodes due to ocean currents and tides is a challenging issue in efficient localisation for underwater acoustic sensor networks. This study therefore proposes a correction method to compensate the error caused by drifting (and accurately localise the target) by introducing an extra floating anchor node. The floating anchor node is placed in the middle of the localisation area and

The decomposition of multi-component micro-Doppler signals overlapping in the time-frequency (T-F) domain is critical and challenging, especially in the case of irregular instantaneous Doppler frequency. The authors propose a novel time-based decomposition method called the short-time variational mode decomposition (STVMD) to analyse the irregular (FM) micro-Doppler signals, and present an optimal

In this study, the authors take further insight into the sparse geometry which offers a larger array aperture than uniform linear array with the same number of physical sensors. A novel direction of arrivals (DOAs) estimation model with flexible sparse geometry, which possesses the potential to significantly improve the estimation performance especially when the placed space and the weight of carrier

Human identification plays a vital role in daily lives. A majority of biometric technologies require the active cooperation of humans, while gait recognition does not. Compared with other identification technologies, radar-based technology can monitor the human body around the clock without being affected by light/weather, and is not easy to be forged while protecting privacy. Previous researches have

Combined sky-wave and surface-wave monostatic high-frequency (CSSM-HF) radar is a new type of mono-static high frequency (HF) radar that uses multiple combined propagation modes of skywave and surface wave to detect targets. However, the detection range of different propagation modes partially overlaps, which results in multiple mode echoes from one target. To track the target in the presence of multi-mode

The derivation of tight estimation lower bounds is a key tool to design and assess the performance of new estimators. In this contribution, first, the authors derive a new compact Cramér–Rao bound (CRB) for the conditional signal model, where the deterministic parameter's vector includes a real positive amplitude and the signal phase. Then, the resulting CRB is particularised to the delay, Doppler

The authors propose an algorithm to estimate the path followed by refracted signals from a source to a target, through a medium formed by uniform parallel layers with known different refractive indices, a common model used for ice radio-echo sounding. The analytical solution is a polynomial with a degree that exponentially depends on the number of layers, being computationally inefficient. For low

An adaptive extend Kalman filter（EKF） is designed to estimate the roll angle for trajectory correction projectile only using radial magnetometers. By analysing the characteristics of the radial magnetometer output signal and the complex angular motion of the high-spin projectiles, the measurement equation is established. Two important measures, namely noise parameter adaptation and increasing system

Cognitive radars have the capability of adapting the transmitted waveform with the dynamic state of target and environment, to enhance the radar performance. In this study, a cost function is proposed for designing the waveform parameters in cognitive radars, along managing the radar time resources. The proposed cost function has the capability of adapting to any radar measurement vector. The purpose

Underdetermined wideband direction of arrival (DOA) estimation based on the sparse array is studied here and a novel algorithm is developed to improve the estimation performance of off-grid targets in the framework of sparse Bayesian learning. First, the narrowband off-grid model is extended to a wideband case and the sparse Bayesian model containing off-grid biases is deduced. Then, a sequential solution

With the multi-function need for airborne space-time adaptive processing (STAP) radar, range synthesis is usually necessary for the follow-up function of target recognition. Utilising the excellent performance on orthogonality and bandwidth synthesis of the frequency division multiple access (FDMA) waveform and the longer accumulation time of multiple-input multiple-output (MIMO) radar, a robust low-sidelobe

The construction of the third generation of the Chinese BeiDou navigation satellite system (BDS), which provides global positioning, navigation, and timing (PNT) services, will be completed in 2020. As BDS satellites contain the geostationary orbit (GEO), inclined geosynchronous (IGSO), and medium earth orbit (MEO), orbital manoeuvres occur more frequently. Thus, orbit manoeuvre detection is important

Based on the mean arrival time and temporal broadening of pulsed waves propagating through turbulent media, this study investigates the ionospheric effects induced by irregularity on medium-earth-orbit synthetic aperture radar (MEOSAR) range imaging quality. Considering radar signal two-way propagating through ionosphere irregularity, an analysis model for ionospheric effects induced by irregularities

Cognitive radars have the capability of using the prior environmental information to improve the radar performance. In this study, a cost function for fully adaptive waveform parameters design for cognitive tracking radars is proposed. These parameters include – but not limited to – pulse length, pulse repetition frequency, number of transmitted pulses, and target revisit rate. Thus, the proposed cost

This study proposes an intelligent tracking method based on the expectation maximisation approach. To obtain the consistent tracking performance, the observer should maintain contact with the target and continuously update its tracking data. Unfortunately, a significant problem arises from the uncertainty of the target motion. The reasons behind this uncertainty include losses, time-varying noises

High-frequency surface wave radar (HFSWR) is an effective method for detecting and monitoring the targets on the ocean surface and above. To improve the detection performance of HFSWR, a new detector is proposed by applying weighted distance iteration (WDI) processing to the joint domain localised (JDL) matrix constant false alarm rate (CFAR) detector. Based on information geometry theory and Riemannian

Gait-based human identification aims to identify individuals by their walking style. In this study, the authors investigate the use of micro-Doppler (m-D) signatures retrieved from a frequency-modulated continuous-wave radar sensor to identify individuals based on their natural gait characteristics. The gait dataset of 20 persons has been collected in an indoor environment where each subject was allowed

With the development of estimation algorithms for polarisation sensitive array (PSA) parameters, research has been focused on complete/incomplete electromagnetic vector sensor (EMVS) that is mainly based on electrically ‘short’ dipoles and/or electrically ‘small’ circular loops. Recently, electrically ‘long’ dipoles and electrically ‘large’ circular loops are further preferred and have been proposed

This study introduces a cognitive radar system for autonomous robotic navigation and presents results of simulations and experiments. The study focuses on the role of memory within autonomous cognitive radar systems, examining the impact that working memory has on navigation performance. A suitable radar architecture is derived, inspired by basic natural cognitive processes. It is then implemented

The presence of speckle, a granular structure, seriously affects the visual interpretability of the synthetic aperture radar (SAR) images. Recently, model-based reconstruction techniques that use alternating direction method of multipliers (ADMM) have been widely utilised for denoising problems. Owing to the modular structure of ADMM, it is very simple to implement and also enables one to plug in any

Most existing work on radar classification of micro-drones assumes that the received signal is wholly reflected from a single micro-drone. However, when there are multiple micro-drones in the observed scene, the superimposition of their micro-Doppler signatures increases the classification difficulty. In particular, it is even more challenging to determine if a specific type of micro-drones exists

This study proposes a robust wideband beamforming algorithm based on spectrum separation at divided subspaces to address the possible sensors array manifold deviations in practice. In this algorithm, an efficient sensors array manifold calibration approach based on subspace division is put forward and an improved interference-noise covariance matrix reconstruction approach based on spectrum separation

As an indispensable part of electronic support measure, the de-interleaving technique is used to separate interleaved radar pulse streams. At present, clustering based on radar features is one of the most effective de-interleaving methods. In a dynamically varying electromagnetic environment, the features of intercepted radar pulses overlap each other. Compared with other de-interleaving algorithms

Frequency diverse array (FDA) as a new array technology with range-, angle- and time-dependent beamforming has received much attention, especially in the application of radar systems. In FDA, the element indices employed frequency increments to produce angle–range beamforming. This study proposes bat metaheuristic algorithm-based synthesis technique to uncouple the FDA angle–range beamforming. Specifically

Recognition of multi-function radar (MFR) work mode in an input pulse sequence is a fundamental task to interpret the functions and behaviour of an MFR. There are three major challenges that must be addressed: (i) The received radar pulses stream may contain an unknown number of multiple work mode class segments. (ii) The intra-mode and inter-mode knowledge of a modern MFR may be too flexible and complicated

A clutter suppression method based on a combined method of clutter map and K-SVD algorithm has been proposed, which aims at reducing false alarm rate of air surveillance radar caused by wind farm clutter. First, a clutter map, based on the fixed position and Doppler spectral width characteristics of wind turbines, is established using constant false alarm rate detection. The obtained clutter map is

The identification of bird size from radar echoes is a mission in radar ornithology. Yet, neither radar cross-section nor wingbeat frequency measured from radar signals of birds is good recognition discriminant. In this study, the authors propose that large birds habitually carry their feet stretched out behind them during flight, leaving their feet apart from the body and being recognisable to both

Multiple-input multiple-output (MIMO) array synthetic aperture radar (SAR) can be used to directly obtain the three-dimensional (3D) imagery of the illuminated scene with a single track. Due to the length limitations of synthetic aperture and antenna array, the super-resolution algorithms within the framework of 2D compressive sensing (CS) have been conceived to reconstruct the azimuth-cross-track

A novel integrated waveform (IW) for continuous active sonar detection and communications is proposed in this study based on a generalised sinusoidal frequency-modulated signal. This study first introduces the mixed modulation of the IW and a model for the transmitting signal, and then it analyses the time and frequency resolution and anti-reverberation capability of the proposed IW. The performance

Vision-aided inertial navigation (VAIN) is a prospective technique for determining the pose of the spacecraft during asteroid missions. The VAIN system can fuse the inertial and visual data by employing the high-degree cubature Kalman filter (HCKF) because it can accurately handle non-linear problems. However, the visual measurements can be corrupted by non-Gaussian noise with unknown time-varying

Although interferometric radar altimeter (IRA) provides accurate three-dimensional terrain information, it is difficult to eliminate some IRA uncertainties by signal processing. This calls for a filter that possesses strong robustness against outliers. An auxiliary particle filter (APF), which can be used to perform terrain referenced navigation using IRA technology as an alternative to an integrated

In this study, the authors mainly explore the relationship between the data quality of smartphones equipped with global navigation satellite system (GNSS) modules and the accuracy and reliability of single-frequency real-time kinematic (RTK) positioning. Specifically, the visible satellite number, code minus carrier and the signal-to-noise ratio of the GNSS raw observations were evaluated through static

The authors consider radar classifications of activities of daily living, which can prove beneficial in fall detection, analysis of daily routines, and discerning physical and cognitive human conditions. They focus on contiguous motion classifications, which follow and commensurate with the human ethogram of possible motion sequences. Contiguous motions can be closely connected with no clear time gap

A low-complexity method based on the second-order direct infinite impulse response (IIR) notch and its cascaded form for global navigation satellite systems (GNSSs) is proposed to mitigate the continuous wave interference (CWI) and narrowband interference (NI) as well as their mixed interference. The number of the cascaded stages is selected by the bandwidth of NI as well as that of the second-order

Pulse repetition frequency (PRF) staggering is a well-established technique in the pulse-Doppler radar, used in order to increase the unambiguous range and Doppler and to minimise blind spots. The study offers a new staggering dimension that can increase the number of different staggering choices. The new approach is to add an inter-pulse coherent phase-coded overlay. The code is shorter than the number

The effects of complex electromagnetic environment on a radar system involve many factors and their interrelationships are also complicated, so it is difficult to quantitatively describe the impact of jamming on the radar. In this study, the authors start from the signal models of several jamming types and the basic signal processing flow of pulse-Doppler radar and propose a unified evaluation framework

The iterated-corrector probability hypothesis density (IC-PHD) filter propagates the posterior intensity of each sensor at one time step to improve tracking accuracy. However, targets cannot be estimated by the IC-PHD filter, if the detection probability of the last update sensor is low. To deal with this problem, this study presents a new multi-sensor multi-target tracking method. Analysing the iterative

A new approach for the synthesis of one-dimensional (1D) and 2D reconfigurable sparse arrays generating sum and difference power patterns is presented in this study. In the case of 1D arrays, the design procedure provides solutions in which only one set of amplitude coefficients is required and the reconfigurability is obtained by modifying only the excitation phases. In the case of 2D arrays, the

This study proposes an advanced direction-of-arrival (DOA) estimation method for automotive multiple-input multiple-output (MIMO) fast-ramp radar systems. To distinguish the transmitted signal at the receiving antenna, the orthogonal code can be applied to each transmitted signal. In this case, to correctly estimate the angles of the targets, the authors also have to match the distinguished signals

Low-cost signal jammers, which are illegal in many countries but continue to be traded in the black market, emit weak global navigation satellite system (GNSS) jamming signals. This study proposes a method to detect, identify, and localise these signals based on a cloud-data processing technique in which the jamming detection, identification, and localisation are performed sequentially after gathering

The instantaneous kinematic velocity obtained by using a stand-alone global navigation satellite system (GNSS) receiver has attracted increasing attention, and has significant for numerous applications. Using the time difference carrier phase (TDCP) measurements, or the displacements they produced, we propose two real-time instantaneous velocity determination methods based on the moving-window polynomial

The signal separation method based on the short time Fourier transform (STFT) and the L-statistics can effectively eliminate the interference of the micro-Doppler effect on inverse synthetic aperture radar (ISAR) imaging. The insufficient frequency resolution of STFT will result in poor interference cancellation when the azimuth range between two adjacent scatterers is small. Then, a novel method for

An active sensing system, such as radar, extracts the useful features of the targets of interest, by transmitting a certain waveform to a particular area and analysing the returned signal. There are two factors that are critical to the system performance, namely the receive filter and the transmitted waveform. Transmitted signal is among the most interesting factor affecting the radar system performance

This study considers the Bayesian programming methodology for recognition and classification of radio emission sources. A mathematical model of Bayesian programming proposes forming a family of probability distributions based on known parameters contained in a training sample (database). The correlations between the object classes have been estimated according discussed methodology. The received assessment

Time delay estimation (TDE) between receivers plays a significant role in various fields such as radar, sonar, global positioning system, and underwater communications. TDE is the first step in the localisation and tracking of the source. Estimation of the time delay of a passive sonar system in a reverberant environment is one of the most challenging tasks. For some decades, the well-known generalised

The increasing amount of space debris poses a growing challenge in the development of space travel. In previous work, a proposed system comprising of a low budget space-borne passive radar based on CubeSAT, flying in Low Earth Orbit (LEO), demonstrated promising results in terms of space debris detection performance. In this work, a novel shadow inverse synthetic aperture radar (SISAR) model for space

The carrier phase (CP) technique based on the global positioning system is a widely applied spatial tool for precise time and frequency transfer. However, the traditional CP technique considers the receiver clock offset to be a white noise stochastic process, which introduces unknown errors into the model and thereby compromises time and frequency transfer performance. To improve the performance of

Phase adjustment with the autofocus process is essential to inverse synthetic aperture radar (ISAR) imagery of manoeuvring targets. Conventional parametric and non-parametric autofocus methods usually degrade in front of error model mismatch and noise interference. Especially, the target manoeuvre also induces higher order phases that have the spatial-variant characteristic. In this study, a range-dependent

The mutual interference between frequency-modulated continuous-wave (FMCW) automotive radars increases the noise floor, even submerges the information of targets, and creates ghost targets. To reduce the impact of the mutual interference between automotive radars and improve the detection performance, this study proposes an iterative modified threshold method based on empirical mode decomposition (IMT-EMD)

Image matching is an important step that is taken in most synthetic aperture radar (SAR) images applications. In this study, a method is proposed for texture image reconstruction to improve SAR image matching. This method consists of three major steps. First, textural features are extracted. Second optimal texture images (OTIs) are created using extracted features. Texture optimisation is conducted

This study considers the 3D scenario where an autonomous underwater vehicle (AUV) tracks an emitter while estimating the emitter's location by measuring the emitter's frequency and elevation–azimuth angle. To enhance the emitter estimation based on frequency–angle measurements, this study presents an AUV's path planner considering acceleration limits, such as the bounded turn rate. As far as the author's

This study considers cooperative localisation and exploration of multiple unmanned underwater vehicles. The author assumes that one vehicle, called the communication/navigation aid (CNA), moves near the sea surface and that the vehicle can use a global positioning system (GPS) to localise itself. To explore a deep sea, the author's strategy is to make each vehicle move at a distinct depth such that

Forecasting of total electron content (TEC)/global positioning system (GPS) signal delays in storm conditions is considered the most challenging task for accurate position estimation, especially in critical applications. Therefore, a storm-time ionospheric model is proposed to forecast TEC based on the artificial neural network (ANN) using singular spectrum analysis (SSA). The study area covers four

In the underwater sound source localisation systems, the sound wave signal is accompanied by time delay and Doppler shift, where the cross-ambiguity function (CAF) is commonly applied as a method of estimating them. This study proposes a novel method for calculating the exact value of the CAF,based on the theory of curved surface interpolation. Firstly, two optimisation problems with equality and inequality

Sparse representation can be extended to high dimensions and can be used in many applications, including three-dimensional (3D) Inverse synthetic aperture radar (ISAR) imaging. In this study, the high-dimensional sparse representation problem and a recovery method called high-dimensional smoothed least zero-norm (HDSL0) are formulated. In this method, the theory and computation of tensors and approximating

Learning discriminative features is difficult for deep learning-based target recognition in synthetic aperture radar (SAR) images with small training samples. To achieve a better feature learning, this study proposes a new deep network, a compact convolutional autoencoder (CCAE) for SAR target recognition. CCAE minimises the reconstruction loss and the distance between intra-class samples simultaneously

Initial relative parameters are of great importance as inputs of the subsequent filter process based on the stereovision system. The relative dynamic model is approximated to estimate the initial relative state. Firstly, the error distribution property of feature point captured using cameras can be approximately regarded to be zero-mean Gaussian distribution when the measurement error of pixel is assumed