The goal of maritime situational awareness (MSA) is to provide a seamless wide-area operational picture of ship traffic in coastal areas and the oceans in real time. Radar is a central sensing modality for MSA. In particular, oceanographic high-frequency surface-wave (HFSW) radars are attractive for surveying large sea areas at over-the-horizon distances, due to their low environmental footprint and

Ionospheric phase contamination deteriorates the coherence of high-frequency echoes, reducing the detection performance of multiple-input multiple-output over-the-horizon radar (MIMO-OTHR) on slow ships. A high-precision phase decontamination method approximately extracts a single-frequency reference signal from the echo in advance, called the calibration signal, which is completed in the Doppler domain

Synthetic aperture radar (SAR) image classification is one of the most important subjects in automatic target recognition. Therefore, identifying the correct class of targets has significant importance to take a decision. Recently, several deep learning techniques, especially the convolutional neural networks (CNNs), have improved the SAR images classification performance due to its powerful perspective

In order to realise the fast detection of ships in synthetic aperture radar (SAR) images, a detection method combining visual saliency and a cascade convolutional neural network (CNN) is proposed. First, based on visual saliency, a multiscale spectral residual model is designed for realising the fast detection of ship candidate regions. Then, a cascaded CNN is designed, which consists of two convolution

By forging global navigation satellite system (GNSS) signals similar to authentic ones, a spoofer can make receivers track forged signals (spoofing signals) and generate wrong position, velocity and time results. Receiver autonomous integrity monitoring (RAIM) can be extended to the field of spoofing detection and exclusion (SDE). However, it is well known that when there are six or more signals and

The traditional method considers the Sun as a rigid sphere and diffuse radiator, and neglects the solar characteristics. However, this leads to high bias in the measurement model. In this study, to build a more realistic bias model and a statistical model of noise, the authors consider three solar characteristics, including the solar differential rotation, Lambert radiator and small-scale solar activities

Costas signals are widely used in modern radar systems as frequency coded. The Costas-code-based waveform can achieve a nearly thumbtack shape of the ambiguity function (AF). However, the highest AF's sidelobe levels (SLLs) of Costas waveform equals just 1/ N times of its main lobe level height, where N is the length of the Costas code. In this study, the authors suggest a generalised Costas waveform

The electronic support measure has a pivotal role in electronic warfare. Radar signal deinterleaving achieves complex radar pulse streams to deinterleave by analysing the intercepted radar emitter signals and estimating the pulse repetition interval (PRI) values. At present, most of the deinterleaving algorithms use the classical model of pre-sorting combined with the PRI deinterleaving algorithm,

In this study, a multi-polarised two-dimensional (2D) planar array of sparsely located vector antennas (VAs) is designed for the block sparse representation (SR)-based 2D direction finding and polarisation parameter estimation of wideband signals. In order to alleviate the inter-VA mutual coupling effect, the minimum inter-VA spacing of the 2D sparse array is constrained to be no less than one wavelength

Robust object detection in sonar images is an important task for underwater exploration, navigation and mapping. Current methods make assumptions about the shape, highlight or shadow of an object, which may be invalid for some environments or targets. We focus on the area of feature extraction-based detection, which does not rely on information about the shape of the target, towards a robust framework

A multi-sensor fusion approach for simultaneous localisation and mapping (SLAM) based on a bio-inspired polarised skylight sensor is presented in this study. The innovation of the proposed approach is that a newly designed bio-inspired polarised skylight sensor, which is inspired by the navigation principle of desert ant, is introduced to improve the accuracy of SLAM. The measurement equations based

Aircraft wake is a pair of strong counter-rotating vortices generated behind a flying aircraft, which might be dangerous to the following aircrafts. The real-time and precise locating of aircraft wake vortex-core positions is essential in the aviation safety field, especially in airport traffic management. This study proposes a two-step vortex-core locating method which uses the Gabor filter to make

In a vector tracking loop (VTL) architecture, non-linearities exist in discriminator functions and pseudo-range/pseudo-range rate measurement expressions. Generally, normalisation functions are used in discriminators to export the desired code phase or carrier frequency error and the extended Kalman filter is adopted to estimate receiver's states. This process could be accurate enough when the code

Some new problems in distributed inverse synthetic aperture radar (ISAR) fusion imaging may be caused by constant frequency errors (CFE) due to the imperfect match of two independent oscillators. In this study, the effects of the CFE on distributed ISAR coherent fusion imaging are first analysed, which show that the CFE will produce false images (incorrect scatterer number and position) in distributed

Space–time adaptive processor based on power inversion (PI) criterion can effectively suppress interference for the global navigation satellite system (GNSS) receiver when the steering vector of the GNSS signal is unknown. However, existing space–time PI processing methods will introduce meter-level pseudo-code tracking biases into the GNSS receiver measurements which cause several meter-level position

Air-to-ground ranging (AGR) is one of the important operation modes of an airborne monopulse radar system. Here, an approach for the detailed modelling and simulation of the AGR performance of such a radar system over complex terrain is proposed. Time-domain monopulse signals reflected by the terrain's surface were modelled using the dynamics of the airborne platform, clutter properties, and RF specifications

Compared with conventional phased array radar, the collocated multiple-input multiple-out (C-MIMO) radar is envisioned to offer greater freedom in waveform design and can simultaneously manage different beams to track multiple targets in the simultaneous multi-beam (SM) working mode. In this study, aiming at the multiple targets tracking (MTT) problem, a joint beam selection integrated with power and

This article considers autonomous scanning (coverage) control of a two-dimensional (2D) surface embedded in 3D environments. The author uses a robot with rigidly mounted range sensors. The robot can measure its depth (height for aerial robot) and has narrow aperture rays near the central ray which is normal to the longitudinal axis of the robot. The goal of the robot is to scan (cover) a 2D surface

An underwater acoustical navigation (UWAN) system is widely used on an autonomous underwater vehicle (AUV). The navigation error prediction is of great significance to the design, use, and capability upgrade for the UWAN system. Owing to the trend of faster AUV and the need for higher navigation accuracy, traditional navigation models are mismatched. Besides, they adopt fixed input errors (including

Performance of global navigation satellite systems (GNSSs) mounted on aerial platforms could be degraded by the presence of jamming or spoofing threats. Detection of jamming and spoofing is essential considering practical applications of satellite navigation in passenger aircrafts, unmanned aerial vehicles (UAVs), helicopters and fighters. Different algorithms and methods have been proposed for detection

In this study, the authors propose for the parameter estimation of chirp signals at low signal-to-noise ratios using the spectrum phase instead of the traditional temporal phase. First, the spectrum phase expression of chirp signals is derived, which demonstrates that the spectrum phase can be approximated as a quadratic function of the frequency. However, the spectrum phase is a wrapped phase modulo

Synthetic aperture radar (SAR) images for automatic target classification (automatic target recognition (ATR)) have attracted significant interest as they can be acquired day and night under a wide range of weather conditions. However, SAR images can be time consuming to analyse, even for experts. ATR can alleviate this burden and deep learning is an attractive solution. A new deep learning Pose-informed

A spectral algorithm for processing staggered-pulse repetition time (SPRT) signals in weather radar is introduced. It includes new approaches for ground clutter filter and hydrometeor spectral moments estimation. The algorithm uses ideas similar to GMAP but applied to non-uniform sampled signals. This work is focused on staggered sequences 2/3, but can be extended to other staggered sequences. Monte

The fifth-degree cubature Kalman filter (5D-CKF) has been recently developed for both the discrete- and continuous-time non-linear stochastic systems. In the published works, it has been mentioned that numerically stable square-root 5D-CKF implementations are not feasible to derive, although they are easily obtained for the third-degree CKF. The key problem of the underlying mathematical derivation

Target localisation is one of the key technologies and a performance metric in underwater acoustic sensor networks. A number of range-free and range-based localisation algorithms are proposed. Among them a range-based localisation algorithm: weighted centroid localisation (WCL) is widely used due to the relatively simple implementation and better localisation. The accuracy of WCL, however, is reduced

The state of the signal in space (SIS) broadcasted by the broadcast ephemeris will affect the reliability and safety of the user navigation and positioning. Understanding the SIS anomaly of a satellite is conducive to fault allocation in advanced receiver autonomous integrity monitoring. In this study, precise ephemeris was used to calculate the SIS error of all healthy Galileo satellites from 2017

Underwater acoustic imaging (UAI) can be utilised to observe the spatial distribution of a near-field sound source. The image quality depends on the resolution and sidelobe level of conventional beamforming. The linear array-based UAI can be considered as deconvolution of a two-dimensional point spread function shift-variant model. The performance of UAI can be improved via innovative deconvolution

To improve the stability and accuracy of manoeuvring target tracking in three-dimensional space based on the angle of arrival (AOA) and its rate of change observations, this study presents a new observation fusion method by fusing the received signal strength (RSS) with AOA and the rate of change of AOA. To enhance the adaptive ability of traditional strong tracking extended particle filter (TSTEPF)

Imaging of multiple maritime moving targets is a challenging task in the synthetic aperture radar (SAR) system owing to the fact that the complex target motion produces evident image defocusing. Given that the sparsity of ship targets in the SAR image, the authors propose a new imaging method of multiple maritime moving targets based on sparsity Bayesian learning. To avoid the overcomplete velocity

Real-time single-frequency precise point positioning (RT-SFPPP) of low-cost has been attracting increasing attention in numerous global navigation satellite system (GNSS) applications. Nowadays, three multi-GNSS RT-SFPPP models are widely applied, i.e. ionosphere-corrected (IC), ionospherefree (IF) and ionosphere-weighted (IW) models. A comprehensive evaluation of the three models using CLK93 products

This work addresses the problem of integrating a new signal in the Galileo E1 band. Thus, the arising question is how the existing multiplexing methods can be efficiently used or modified to integrate a new binary signal in the Galileo E1 band with the existing Galileo E1 signals. To this end, in this study, the authors first select three efficient multiplexing methods from the state of the art (i

In this study, the authors address the problem of range-distributed target detection in sequential high resolution range profiles (HRRPs). They propose a modified scaled largest eigenvalue detector for static target in homogenous ground clutter. A set of secondary data, which are free of target signal and have the same distribution as the clutter in the primary data, are assumed to be available. First

The authors introduce a constant false alarm rate (CFAR) detection algorithm, called K-CFAR, for automatic detection of underwater objects in sonar imagery. The K-CFAR adopts the K -distribution as a statistical model of the background. An efficient closed-form estimator for the K -distribution parameters is derived by the second-order approximation of the Polygamma function without involving a numerical

Bats and birds are endangered by wind turbines, leading to a significant amount of fatalities in recent years, mainly due to a direct collision of the animals with the rotor blades or through barotrauma effects. The search for fatalities and the quantification of their number is an important tool to understand the adverse effects of wind turbines on bats and birds. This method has several problems:

This work deals with the entire process of target detection and ranging by a sky-wave over-the-horizon radar (OTHR) computational model simulation. The different processing stages of the transmitted signal along its space–time trajectory from transmission to digital signal processing are modelled. With this simulation tool a moving target present over the sea can be detected according to a set of given

A distance selective pseudo-random noise (PRN)-coded Doppler radar is proposed. The radar is capable of measuring the vital signs of a human in a noisy environment with high precision. The distance selectivity feature is achieved by the use of PRN modulation to focus on the desired target at a certain distance and suppress the Doppler frequencies of other targets at different distances. In addition

In classical beamforming techniques such as minimum mean squared error and minimum variance distortion-less response, for computing optimum weight vector of an antenna array, direction of arrival (DoA) of desired signal should be known as prior knowledge. In this study, a deep neural-network-based beamformer is proposed for estimating the desired signal in presence of noise and interference without

Current target tracking algorithms for wireless sensor networks in noise environments have large positioning errors. Owing to the environmental noise, Kalman filters (KFs) are used to estimate the target position. To reduce the adverse effect of unknown or time-varying noise on KFs, adaptive KFs (AKFs) are developed. However, the present AKFs can only achieve second-order estimation accuracy. To improve

Moving targets in synthetic aperture radar (SAR) imagery often yield signatures that are smeared beyond recognition. One mitigation strategy is to attempt to refocus such smears as if the corresponding targets were stationary. This problem is especially difficult for cases in which the target executes time-varying rotation rates for roll, pitch and yaw, as well as for simultaneous non-linear target

Self-localisation is vital for autonomous vehicles. In this study, the authors present an augmented extended Kalman filter (AEKF) framework for intelligent vehicle localisation applications. Compared to the previous approach, the proposed AEKF is enhanced through a model fusion, which incorporates a constant velocity model, constant acceleration model, constant turn rate and velocity, and constant

In this study, an attempt is made to develop regional ionospheric total electron content (TEC), rate of TEC index (ROTI) and amplitude scintillation index ( S 4 ) maps using data from 26 dual-frequency global positioning system (GPS) receivers under GPS aided geo-stationary earth orbit augmented navigation programme over Indian region. One-minute spatial TEC maps are generated for the entire Indian

This study presents an unknown-but-bounded (UBB) model approach to robust extended Kalman filtering (REKF) problem for the simultaneous input and state estimation of non-linear systems with parametric uncertainties. An augmented non-linear state-space model is suggested to estimate the unknown input concurrently with the state variables without any delay. Due to more satisfactory physical assumptions

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