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The algorithm proposed in this paper jointly selects the transmitted waveform and the control input so that a radar sensor on a moving platform can prosecute a target by minimising a predefined cost that accounts for the energy of the transmitted radar signal, the energy of a platform control input and the relative position error between the platform and the target. The cost is a function of the waveform design and control input. The algorithm extends the existing Joint Waveform Guidance and Control Optimization (JWGCO) solution to nonlinear equations to account for the dependency of the radar measurement accuracies on Signal to Noise Ratio (SNR) and, as a consequence, on the target position. The performance of the proposed solution based on statistical linearisation is assessed with a set of simulations for a pulsed Doppler radar transmitting linearly frequency modulated chirps.

Radars monitoring small targets often must increase their integration times to achieve sufficient signal-to-noise ratio (SNR) for maintaining a viable track. These longer integation times can prevent micro-Doppler signature extraction and instead result in Doppler signatures consisting of spectral lines to the radar's higher-level processing. Whether the radar operates in the micro-Doppler or spectral line regime depends on both radar parameters (e.g. waveforms, wavelengths and integration times) as well as target parameters (e.g. rotor length, rotational frequency, target reflectivity and geometry). Additionally, understanding the transition region between these regimes can further aid target recognition algorithms. This paper uses modelling, simulations and experimental data to refine the understanding of how a particular radar will observe a target Doppler signature in either of these regimes, highlighting the transition region between the two.

Nano-drones, are insect-like size drones with a capability of intrusion to provide intelligence and potentially violate secure establishments and public privacy rights. Nano-drones are already an existing technology which is becoming more and more available, portable, affordable and easily operated. As such, they may soon become a plausible defence and security threat. This paper presents the design and development of a K-Band FMCW radar prototype for nano-drone detection. The FMCW radar prototype consists of connectorised components operating at a carrier frequency of 24 GHz and offer high parameter selection flexibility. Experiments have been carried out in order to evaluate the system performance. Results show that a small Arcade PICO Drone Nano Quadcopter (smaller than 5 cm) could be detected, and that its micro-Doppler signature could be extracted from data.

Staring radars use a transmitting static wide-beam antenna and a directive digital array to form multiple simultaneous beams on receive. Because beams are static, the radar can employ long integration times that facilitate the detection of slow low-RCS targets, such as drones, which present a challenge to traditional air surveillance radar. Typical low altitude trajectories employed by drones often result in low-grazing angle multipath effects which are difficult to mitigate with a monostatic radar alone. The use of multiple spatially separated receivers cooperating with the staring transmitters in a multistatic network allows multi-perspective target acquisitions that can help mitigate multipath and ultimately enhance the detection of drones. This paper investigates how varying the network geometry affects the estimation performance of a targets position and velocity in a multipath free scenario. The optimal geometry is found by minimising the trace of the Cramer-Rao Lower Bound (CRLB) of the Maximum Likelihood (ML) estimates of range and Doppler using the Coordinate Descent (CD) algorithm. The network estimation accuracy performance is verified using Monte Carlo simulations and an ML Estimator on the target parameter estimates.

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 architecture solution, that takes into account the impact of target orientation on the SAR image as the scatterers configuration changes, is proposed. The classification is achieved in two stages. First, the orientation of the target is determined using a Hough transform and a convolutional neural network (CNN). Then, classification is achieved with a CNN specifically trained on targets with similar orientations to the target under test. The networks are trained with translation and SAR-specific data augmentation. The proposed Pose-informed deep network architecture was successfully tested on the Military Ground Target Dataset (MGTD) and the Moving and Stationary Target Acquisition and Recognition (MSTAR) datasets. Results show the proposed solution outperformed standard AlexNets on the MGTD, MSTAR extended operating condition (EOC)1, EOC2 and standard operating condition (SOC)10 datasets with a score of 99.13% on the MSTAR SOC10.

Multibeam radar (MBR) systems based on waveform diversity require a set of orthogonal waveforms in order to generate multiple channels in transmission and extract them efficiently at the receiver with digital signal processing. Linear frequency modulated (LFM) signals are extensively used in radar systems due to their pulse compression properties, Doppler tolerance, and ease of generation. Here, the authors investigate the level of isolation between MBR channels based on LFM chirps with rectangular and Gaussian amplitude envelopes. The orthogonal properties and the mathematical expressions of the isolation are derived as a function of the chirp design diversity, and specifically for diverse frequency slopes and frequency offsets. The analytical expressions are validated with a set of simulations as well as with experiments at C-band using a rotating target.

The negative effects wind farm clutter has on the performance of radar systems for Air Traffic Control and Air Surveillance is well-known in the radar research community and several mitigation techniques have been proposed to address this problem. These include bistatic and multistatic radar systems providing multiple views of the area under surveillance, and hence potential additional information that can be used to improve the receiver performance. This paper presents the analysis of a set of experimental data collected simultaneously by two radar systems, one operating at S-band and one at X-band, of echoes from an operational wind farm in the UK near Oxford. This analysis presents several parameters extracted from the time domain data and the Doppler spectra, such as Doppler centroid and bandwidth of the micro-Doppler signature as well as amplitude statistics of the time domain returns. These parameters are characterised using data recorded at monostatic and bistatic nodes, as well as at different polarisation combinations.

In DRAGON, novel 3-D-shaped conformal antenna arrays are investigated to exploit the ability of an RF seeker to diversify, select and optimize the transmitted waveform design and the 3-D phased array beam-pattern characteristics on a scan to scan basis.The goal of DRAGON is to develop a new solution, which is based on the use of 3-D conformal antennas that are capable to operate with different waveform parameters. Optimization of waveform parameters will provide a strategy to improve prosecution trajectories.

This paper presents results of an experimental trial aimed at detecting a car and a flying drone, passively, by exploiting transmissions of opportunity from a staring Holographic radar. Results show that targets could be successfully detected using a low-cost passive receiver prototype. This may be considered a first step towards a radar network that could provide more comprehensive coverage, over a wider area, against a broader set of target types and without requiring additional spectral resources.

The algorithm developed in this paper jointly selects the optimal transmitted waveform and the control input so that a radar sensor on a moving platform with linear dynamics can reach a target by minimising a predefined cost. The cost proposed in this paper accounts for the energy of the transmitted radar signal, the energy of the platform control input and the relative position error between the platform and the target, which is a function of the waveform design and control input. Similarly to the Linear Quadratic Gaussian (LQG) control problem, we demonstrate that the optimal solution satisfies the separation principle between filtering and optimisation and, therefore, the optimum can be found analytically. The performance of the proposed solution is assessed with a set of simulations for a pulsed Doppler radar transmitting linearly frequency modulated chirps. Results show the effectiveness of the proposed approach for optimal waveform design and optimal guidance control.

Multibeam radars (MBR) enable multiple independent channels by simultaneously exploiting spatial and waveform diversity. The use of orthogonal waveforms is employed to form multiple independent antenna beams, each one providing a different function using diverse radar resources. In this paper, the analytical derivations of the isolation between pseudo-orthogonal rectangular and Gaussian linear frequency modulated (LFM) waveforms are presented. Experiments are conducted to verify the analytical results for chirp pairs with different slopes and various time-bandwidth products at C-band. Experimental results are presented for a direct transmission reception loop and for a moving target to account for Doppler shift contributions.

Missile seekers are becoming increasingly more capable of using Doppler Beam Sharpening (DBS) modes as part of the homing cycle, which requires new countermeasures against this mode. One type of countermeasure, is to create false targets within the seeker DBS image. This paper proposes a jamming technique to generate false targets at a precise location within a seeker DBS image, by both delaying and adding a Doppler shift to received waveforms. The effects of tracking errors on the position of the false target are analysed, both analytically and with simulations and used to assess the practical implementation of the jamming scheme. An experimental DBS system was built to test the effectiveness of the jamming scheme against a platform moving in steps and assess errors caused by incorrectly estimating the seeker trajectory.

Published in IET Radar, Sonar and Navigation. Online first 21/06/2016., The potential for using micro-Doppler signatures as a basis for distinguishing between aided and unaided gaits is considered in this study for the purpose of characterising normal elderly gait and assessment of patient recovery. In particular, five different classes of mobility are considered: normal unaided walking, walking with a limp, walking using a cane or tripod, walking with a walker, and using a wheelchair. This presents a challenging classification problem as the differences in micro-Doppler for these activities can be quite slight. Within this context, the performance of four different radar and sonar systems – a 40 kHz sonar, a 5.8 GHz wireless pulsed Doppler radar mote, a 10 GHz X-band continuous wave (CW) radar, and a 24 GHz CW radar – is evaluated using a broad range of features. Performance improvements using feature selection is addressed as well as the impact on performance of sensor placement and potential occlusion due to household objects. Results show that nearly 80% correct classification can be achieved with 10 s observations from the 24 GHz CW radar, whereas 86% performance can be achieved with 5 s observations of sonar.

Reliable landmine detection is still an unresolved problem. Demining operations are complex activities because of the large variety of existing landmine types, many different possible soil and terrain conditions, and environmental circumstances. Due to its ability of detecting both metallic and non-metallic objects, ground penetrating radar (GPR) is a promising method for detecting landmines that may allow faster and safer operations. As the performance of GPR is mainly governed by the target signature, the potential of discriminating target based on the presence of internal reflections could be a valuable advantage for identification and recognition process. This study demonstrates that from a set of high resolution GPR slices the internal design of the landmine can be properly imaged and characterised, confirming the applicability of the methodology and the validity of such an approach.

International audience; Current RF-seekers use a mechanical system to steer the antenna. Instead, 3D conformal antennas coupled to electronically steering demonstrate strong advantages such as a faster steering and a higher coverage. In this paper, the pros and cons of different 2D and 3D array arrangements, the elements orientation and the beamsteering effect are investigated. As part of the specifications, a high azimuthal invariant directivity and a low ellipticity are sought in the direction of the main lobe.

International audience; Automatic Target Recognition (ATR) is the task of automatically detecting and classifying targets. Recognition using Synthetic Aperture Radar (SAR) images is interesting because SAR images can be acquired at night and under any weather conditions, whereas optical sensors operating in the visible band do not have this capability. Existing SAR ATR algorithms have mostly been evaluated using the MSTAR dataset. 1 The problem with the MSTAR is that some of the proposed ATR methods have shown good classification performance even when targets were hidden, 2 suggesting the presence of a bias in the dataset. Evaluations of SAR ATR techniques are currently challenging due to the lack of publicly available data in the SAR domain. In this paper, we presenta high resolution SAR dataset consisting of images of a set of ground military target models taken at various aspect angles, The dataset can be used for a fair evaluation and comparison of SAR ATR algorithms. We applied the Inverse Synthetic Aperture Radar (ISAR) technique to echoes from targets rotating on a turntable and illuminated with a stepped frequency waveform. The targets in the database consist of four variants of two 1.7m-long models of T-64 and T-72 tanks. The gun, the turret position and the depression angle are varied to form 26 different sequences of images. The emitted signal spanned the frequency range from 13 GHz to 18 GHz to achieve a bandwidth of 5 GHz sampled with 4001 frequency points. The resolution obtained with respect to the size of the model targets is comparable to typical values obtained using SAR airborne systems. Single polarized images (Horizontal-Horizontal) are generated using the backprojection algorithm. 3 A total of 1480 images are produced using a 20 ° integration angle. The images in the dataset are organized in a suggested training and testing set to facilitate a standard evaluation of SAR ATR algorithm

Echolocating bats show a unique ability to detect, resolve and discriminate targets. The Spectrogram Correlation and Transformation (SCAT) receiver is a model of the Eptesicus fuscus auditory system that presents key signal processing differences compared to radar which may offer useful lessons for improvement. A baseband version of the SCAT is used to investigate advantages and disadvantages of bat-like signal processing against the task of target resolution. The baseband receiver is applied to RF experimental data and results show higher range resolution than the reciprocal of the transmitted bandwidth can be achieved for two closely spaced scatterers.

We present an algorithm that allows an interceptor aircraft equipped with an airborne radar to meet another air target (the intercepted) by developing a guidance law and automatically adapting and optimising the transmitted waveform on a pulse to pulse basis. The algorithm uses a Kalman filter to predict the relative position and speed of the interceptor with respect to the target. The transmitted waveform is automatically selected based on its ambiguity function and accuracy properties along the approaching path. For each pulse, the interceptor predicts its position and velocity with respect to the target, takes a measurement of range and radial velocity and, with the Kalman filter, refines the relative range and range rate estimates. These are fed into a Linear Quadratic Gaussian (LQG) controller that ensures the interceptor reaches the target automatically and successfully with minimum error and with the minimum guidance energy consumption.

This Letter presents preliminary results of the analysis of amplitude statistics of wind turbine clutter as extracted from multistatic radar data. It is shown that the T-location-scale distribution provides good fitting of the experimental data, and that there are combinations of bistatic angle and polarisations where the bistatic clutter has more favourable statistics for target detection than the simultaneous monostatic clutter.

The authors present an algorithm that allows an interceptor aircraft equipped with an airborne radar to meet another air target (the intercepted) by developing a guidance law and automatically adapting and optimising the transmitted waveform on a pulse-to-pulse basis. The algorithm uses a Kalman filter to predict the relative position and speed of the interceptor with respect to the target. The transmitted waveform is automatically selected based on its ambiguity function and accuracy properties along the approaching path. For each pulse, the interceptor predicts its position and velocity with respect to the target, takes a measurement of range and radial velocity and, with the Kalman filter, refines the relative range and range rate estimates. These are fed into a linear quadratic Gaussian controller that ensures the interceptor reaches the target automatically and successfully with minimum error and with the minimum guidance energy consumption.

Multiple-Beam Radar Systems (MBRS) based on waveform diversity require a set of orthogonal waveforms in order to generate multiple channels in transmission and extract them efficiently at the receiver using digital signal processing. Chirp signals are extensively used in radar systems due to their pulse compression properties, Doppler tolerance and ease of generation. In this paper, we investigate the level of isolation between two linear frequency modulated (LFM) chirps as a function of the frequency slope and of the chirp starting frequency. Results are derived analytically and verified with a set of measurements at S-band.

In this paper, we derive the Ambiguity Function (AF) of a narrowband and a wideband hyperbolic chirp. We calculate the second derivatives of the squared amplitude of the narrowband Complex Ambiguity Function (CAF) and use them to calculate the Fisher Information Matrix (FIM) of the estimators of the target range and velocity. The FIM is then used to calculate the Cramer-Rao Lower Bounds (CRLB) of the variance of the estimators and to ´ carry out an analysis of estimation performance and a comparison with the case of a liner chirp with a rectangular and a Gaussian amplitude modulation. The analysis and the calculations of the CRLB are also extended to a train of hyperbolic chirps. Results corroborate that at narrowband the hyperbolic chirp is less Doppler tolerant than the linear chirp and show that the hyperbolic chirp provides a comparable measurement accuracy to the linear chirp. Results at wideband corroborate the superior Doppler tolerance of the hyperbolic chirp with respect to that of the linear chirp.

Echolocating bats have evolved an excellent ability to detect and discriminate targets in highly challenging environments. They have had more than 50 million years of evolution to optimise their echolocation system with respect to their surrounding environment. Behavioural experiments have shown their exceptional ability to detect and classify targets even in highly cluttered surroundings. The way bats process signals is not exactly the same as in radar and hence it can be useful to investigate the differences. The Spectrogram Correlation And Transformation receiver (SCAT) is an existing model of the bat auditory system that takes into account the physiology and underlying neural organisation in bats which emit chirped signals. In this paper, we propose a baseband receiver equivalent to the SCAT. This will allow biologically inspired signal processing to be applied to radar baseband signals. It will also enable further theoretical analysis of the key concepts, advantages and limitations of the "bat signal processing" for the purpose of target detection, localisation and resolution. The equivalence is demonstrated by comparing the output of the original SCAT to that of our proposed baseband version using both simulated and experimental target echoes. Results show that the baseband receiver provides compatible frequency interference pattern for two closely located scatterers.

Target motions, other than the main bulk translation of the target, induce Doppler modulations around the main Doppler shift that form what is commonly called a target micro-Doppler signature. Radar micro-Doppler signatures are generally both target and action specific and hence can be used to classify and recognise targets as well as to identify possible threats. In recent years, research into the use of micro-Doppler signatures for target classification to address many defence and security challenges has been of increasing interest. In this article, we present a review of the work published in the last 10 years on emerging applications of radar target analysis using micro-Doppler signatures. Specifically we review micro-Doppler target signatures in bistatic SAR and ISAR, through-the-wall radar and ultrasound radar. This article has been compiled to provide radar practitioners with a unique reference source covering the latest developments in micro-Doppler analysis, extraction and mitigation techniques. The article shows that this research area is highly active and fast moving and demonstrates that micro-Doppler techniques can provide important solutions to many radar target classification challenges.