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Nano-drones, are insect-like sized drones with a threat capability of intrusion to provide intelligence and potentially violate secure establishments and public privacy rights. They are an existing technology which is becoming increasingly more available, portable, affordable and easy to operate. As such, they represent a plausible defence and security threat. In this paper, a setup is presented that is used to measure the 3-dimensional Radar Cross Section (RCS) of a nano-drone for three elevation planes with a 5-degree resolution step in azimuth and elevation. The results presented in this paper are unique because there has been very little work, if any, in the existing literature attempting to measure the RCS of such small drones. They are also key to inform further work investigating the development of nano-drone detection radar systems as well as nano-drone detection and classification signal processing solutions.

Staring radars use a transmitting static wide-beam antenna and a directive digital array to form multiple simultaneous beams on receive. Because beams are fixed, the radar can employ long integration times to detect slow low-RCS targets, such as drones, which present a challenge to traditional air surveillance radar. 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 interference, such as signal multipath, and ultimately enhance the detection of drones and reduce target parameter estimation errors. Here, the design of a dual-channel receiver prototype for use in a multistatic cooperative network is presented. Several measurements have been taken using the prototype receiver in a bistatic configuration to test and assess its performance.

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.

The concept of a traditional monostatic radar with co-located transmit and receive antennas naturally imposes performance limits that can adversely impact applications. Using a multiplicity of transmit and receive antennas and exploiting spatial diversity provides additional degrees of design freedom that can help overcome such limitations. Further, when coupled with cognitive signal processing, such advanced systems offer significant improvement in performance over their monostatic counterparts. This will also likely lead to new applications for radar sensing. In this paper we explore the fundamentals of multistatic network radar highlighting both potential and constraints whilst identifying future research needs and applications. Initial experimental results are presented for a 2-node networked staring radar.

Understanding the decision-making process of deep learning networks is a key challenge that has rarely been investigated for synthetic aperture radar (SAR) images. In this article, a set of new analytical tools is proposed and applied to a convolutional neural network (CNN) handling automatic target recognition on two SAR datasets containing military targets. First, an analysis of the respective influence of target, shadow, and background areas on classification performance is carried out. The shadow appears to be the least used portion of the image affecting the decision process, compared to the target and clutter, respectively. Second, the location of the most influential features is determined with classification maps obtained by systematically hiding specific target parts and registering the associated classification rate relative to the images to be classified. The location of the image areas without which classification fails is target type and orientation specific. Nonetheless, a strong contribution of specific parts of the target, such as the target top and the areas facing the radar, is noticed. Finally, results show that features are increasingly activated along the CNN depth according to the target type and its orientation, even though target orientation is absent from the loss function.

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.

Multibeam radars (MBRs) enable multiple independent channels by simultaneously exploiting spatial and waveform diversity. Orthogonal waveforms are employed to form multiple independent antenna beams, each one providing a different function and using different dedicated radar resources. This paper investigates sidelobe levels in MBRs and presents a comparison with those of an Electronic Steerable Array (ESA) that employs a single waveform in transmission to generate multiple simultaneous beams. Simulations are carried out for a 3-channel MBR transmitting quasi-orthogonal Linear Frequency Modulated (LFM) waveforms at Ku band. The response of the MBR to an ideal point target as a function of aspect angle as well as that to multiple targets in different locations has been investigated. Results corroborate the analytical findings and show that the sidelobe levels with respect to angle, at the target range, are attenuated by the cross-ambiguity function properties between the waveforms employed. The range response to a target in low channel isolation suffers from cross-channel interference that may alter the noise floor characteristics of the radar, hence stressing the importance of suitable waveform selection.

Detection and classification of nano-targets (less than 5 cm in size) are becoming important technical challenges as nano-targets are largely invisible to conventional radar. Nano-drones, for example, may soon become a tangible threat capable of providing short-range stealthy surveillance. Similarly, insect pests are posing a significant agricultural risk by causing crop losses and subsequently reducing the yields. Frequency Modulated Continuous Wave (FMCW) radar is a technology that can provide short-range detection, with no blind range and very high resolution, at a relatively low cost. This paper presents the latest results of an ongoing project aiming at designing and developing a low-cost and bespoke 24 GHz FMCW radar prototype to enable detection of nano-targets and extract their Doppler signatures. A home-brew S-band FMCW radar prototype has been initially designed and developed, using off-the-shelf components, to demonstrate the feasibility of our proposed design solution and inform all future activities at 24 GHz. Several experiments have been carried out to test the S-band prototype and assess its performance against larger drones and cars. Results have shown targets could be successfully detected and their micro-Doppler signatures extracted using Short-Time Fourier Transform (STFT) techniques.

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.

Echolocating bats have evolved the ability to detect, resolve and discriminate targets in highly challenging environments using biological sonar. The way bats process signals in the receiving auditory system is not the same as that of radar and sonar and hence investigating differences and similarities might provide useful lessons to improve synthetic sensors. The Spectrogram Correlation And Transformation (SCAT) receiver is an existing model of the bat auditory system that takes into account the physiology and the neural organisation of bats that emit broadband signals. In this study, the authors present a baseband receiver equivalent to the SCAT that allows an analysis of target echoes at baseband. The baseband SCAT (BSCT) is used to investigate the output of the bat-auditory model for two closely spaced scatterers and to carry out an analysis of range resolution performance and a comparison with the conventional matched filter. Results firstly show that the BSCT provides improved resolution performance. It is then demonstrated that the output of the BSCT can be obtained with an equivalent matched-filter based receiver. The results are verified with a set of laboratory experiments at radio frequencies in a high signal-to-noise ratio.

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.

Orthogonal and quasi-orthogonal waveforms are used in a multibeam radar (MBR) to isolate different channels and reduce cross-channel interference. Each channel provides an independent radar beam that performs a specific functionality without interfering with adjacent channels. The MBR signal model is presented that shows how spatial and waveform diversity are employed to successfully separate multiple channels. In this paper, the theoretical predictions of channel isolation are experimentally confirmed with an analysis of micro-Doppler signatures of a rotating target obtained by applying short-time Fourier transform (STFT).

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.

Aveillant Ltd has developed a staring L-band radar that deploys a static quasi-monostatic antenna in transmission and a static digital phased array on receive capable of generating multiple simultaneous beams. Because the antenna is not rotating, the radar can stare at targets and select long dwell times with no effect on the scan rate. High Doppler resolution can be achieved and used to detect small targets, such as drones, even in heavy clutter. Despite the staring array, targets moving with a variable radial velocity generate echoes with a time-varying Doppler frequency shift that limits the integration gain achievable with standard Fourier Transform based techniques. As a result, the number of pulses can be integrated remains limited to the effective coherent processing interval with a consequent suboptimal Signal to Noise Ratio (SNR). This paper presents the results of a set of simulations aimed at studying the integration gain efficiency of a staring radar of the type of the Aveillant Holographic radar for targets moving with a constant and non-constant radial velocity. The case of a target flying horizontally with respect to the radar boresight is investigated to show that compensation techniques can be potentially employed to maximise coherence on the target and the resulting integration gain.

In this study, a feature extraction algorithm is presented which automatically generates a set of shape spectrum features based on the cadence velocity diagram of the human micro-Doppler signature. Recognition performance between humans undertaking the same activity is assessed on a set of experimental data collected with a continuous wave radar operating at X-band using a Naive Bayesian classifier and a shape-similarity-spectrum classifier. Recognition performance is analysed as a function of key parameters, such as the dwell time on the target and the size of the training set, to investigate the level of robustness of the proposed features. Results show that high level recognition performance can be achieved for both the walking and running activities.

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.

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.

Echolocating bats have evolved an impressive ability to detect and discriminate targets in highly challenging environments. It is believed that over 50 million years of evolution have contributed to optimize their echolocation system so that highlevel performance could be achieved within their operating environment. The way bats interrogate the surroundings present differences, as well as similarities, with respect to typical signal processing techniques used in synthetic sensors. In identifying and investigating these differences, useful lessons can be made available to engineers that can potentially be used to improve radar and sonar systems. In this chapter, we review some of the strategies that bats are believed to employ to detect and classify moving and static targets and present a comparison with the radar and sonar counterparts. We introduce a baseband receiver based on an existing model of the bat auditory system and apply it to baseband synthetic ultrasound signals to investigate target detection and resolution performance.

A 3-D staring radar operates by using a wide beam transmitter to illuminate the entire surveillance region and generates multiple receive beams using a 2-D static array that can be digitised at element level. The sensor achieves permanent search in all directions and harnesses the spatial, temporal and spectral domains to improve detection and discrimination of low observable, highly manoeuvrable targets in congested air space against strong non-stationary clutter. While the susceptibility of traditional scanning radars to jammers has been well researched, very little work has been carried out to assess the performance of 3-D staring radars in the presence of an interference source. In this paper, the response of a staring array radar to a jammer is modelled. Results are presented showing that by exploiting the persistent dwell time of the staring array, it is possible to achieve effective jammer suppression using null steering or similar techniques.

In this chapter, we take inspiration from the bat and develop an algorithm that guides an airborne radar interceptor towards a target by jointly developing an optimal guidance 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.

In this chapter, we have presented a baseband receiver that allows an analytical treatment of the output of a SCAT-like processing and that can also be applied to RF signals. The output of the Baseband SCAT (BSCT) has been compared analytically with that of a conventional matched filter for two closely spaced scatterers. Results have shown that a bat-inspired spectrogram transformation can provide better range resolution performance than that of a conventional matched filter. The results have been derived analytically and then verified with a set of laboratory experiments at ultrasound, using phantom echoes and real targets, to assess the robustness of the algorithm with respect to operational hardware limitations and propagation effects.

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.

With the proliferation of low-intensity conflict, landmines have proven to be one of the weapons of choice for both government and guerrilla forces around the world. Recent improvements to mine technology pose increasingly significant problems for demining operations, requiring the constant upgrading of countermine technologies. Ground Penetrating Radar (GPR) is one of the most exhaustively researched topics in the detection of buried mines as it can be used to detect non-metallic and plastic mines. However, identification and recognition are still unsolved problems, due to the scattering similarity between mines and clutter objects. This study provides an experimental evaluation of the improvements that a bistatic approach could yield and what can be gained from investigating the angular dependencies of the landmine radar signature.

Passive Bistatic Radar (PBR) systems use non- cooperative illuminations of opportunity to detect, localise and track targets. The aim of this paper is to investigate the potential of PBR target detection in the presence of non-random signals emitted by non-cooperative transmitters of opportunity, such as radar systems, and without the use of a reference channel. An experiment to detect a moving target was carried out at the Defence Academy of the United Kingdom to demonstrate target detection capabilities using a low cost off-the-shelf receiver. Results show that moving targets can be successfully detected although care must be taken in correcting for frequency offset effects deriving from the non- coherency and non-stability of the receiver local oscillator.

Landmine clearance is a severe and unresolved humanitarian issue. The development of low-cost, smaller, faster and lighter Ground Penetrating Radars (GPR), which can be mounted on unmanned platforms, will allow faster and safer 24/7 operations. This technology will make it possible to survey affected areas with more flexible trajectories and these will provide measurements of landmine signatures from many different aspect angles. As a result, multi-perspective information over wide angular windows and the behaviour of the signature as a function of the angle of illumination can be exploited. Landmine signatures are expected to present features that are less sensitive to the angle of illumination with respect to those of common cluttered objects, and this can lead to an improvement in detection and discrimination performance. In this paper, we present the results of an experimental trial carried out to collect the High Range Resolution Profiles (HRRPs) of two landmines, the SB-33 and the VS-50, off the ground. An analysis of the auto-correlation function of each range bin as a function of the aspect angle is presented together with that of the cross-correlation between profiles collected from different aspect angles.

In this paper, the concept of using Waveform Diversity (WD) with the Doppler Beam Sharpening (DBS) technique for airborne radar systems is investigated with a set of preliminary simulations. WD provides the ability to produce simultaneous multiple beams pointing in various directions without reliance on phase shifters. By using the DBS technique which exploits the Doppler shift of targets within each beam, multiple targets can be resolved and detected within the same range-azimuth cell. The combination of WD and DBS is unique and can provide airborne radar with faster and enhanced coverage, resolution and imaging. This study shows how two orthogonal linear chirps can be used to transmit two simultaneous beams pointing in two different directions with a linear antenna array. It also demonstrates how targets in the same range-azimuth cells can be resolved inside each beam with the combined use of DBS. Insights on critical requirements and directions for future work are also discussed.

The purpose of this paper is to present an experimental trial carried out at the Defence Academy of the United Kingdom to measure simultaneous multistatic and multimodal micro-Doppler signatures of various targets, including humans and flying UAVs. ewline Signatures were gathered using a network of sensors consisting of a CW monostatic radar operating at 10 GHz (X-band) and an ultrasound radar with a monostatic and a bistatic channel operating at 45 kHz and 35 kHz, respectively. A preliminary analysis of automatic target classification performance and a comparison with the radar monostatic case is also presented.

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.

This paper describes a multistatic, sea clutter and vessel database, assembled using the three node, S Band radar, known as NetRAD (for, “Netted Radar”). This data was collected in the United Kingdom and South Africa during 2009-201. It is the intention of the investigators and sponsors of this work to make the raw data available to individuals and organisations interested in processing this multistatic data in support of the development of the understanding of sea clutter and vessel properties in the multistatic configuration.

Bistatic radar is a technique of considerable potential importance and interest. Despite this, current understanding of the properties of bistatic clutter, and in particular, bistatic sea clutter, is limited at best. We present some results of a recent trials campaign to gather bistatic sea clutter data, and to analyse the data in order to develop models to represent bistatic radar sea clutter. The results indicate that the shape parameter of the compound K distribution model fitted to the data tends to be higher for the bistatic clutter than for the equivalent monostatic clutter. This suggests that a bistatic geometry may allow a lower detection threshold for a given probability of false alarm, and hence give improved detection performance of weak targets against a clutter background compared to the conventional monostatic geometry.

Classification of targets by micro-Doppler signatures has attracted a growing interest in recent years. The main bulk translation of a target and additional target motions, such as vibrations and rotations, generate Doppler modulations in the echo that contain unique target features and thus can be used to perform target recognition. Although, target classification by micro-Doppler signatures has been exploited in the RF regime for radar systems, the frequency spectrum is becoming increasingly congested and expensive to use, so that it is desirable to identify and exploit other types which have similar capabilities. In this paper a frequency-agile non-coherent ultrasound radar developed to gather micro-Doppler signatures is presented. This was used in an experimental trial to gather micro-Doppler signatures of personnel targets whilst undertaking various types of motion. Classification performance by these same micro-Doppler signatures is then assessed and results discussed.