Graeme E. Smith

Through-the-Wall Sensing of Personnel Using Passive Bistatic WiFi Radar at Standoff Distances

In this paper, we investigate the feasibility of uncooperatively and covertly detecting people moving behind walls using passive bistatic WiFi radar at standoff distances. A series of experiments was conducted which involved personnel targets moving inside a building within the coverage area of a WiFi access point. These targets were monitored from outside the building using a 2.4-GHz passive multistatic receiver, and the data were processed offline to yield range and Doppler information. The results presented show the first through-the-wall (TTW) detections of moving personnel using passive WiFi radar. The measured Doppler shifts agree with those predicted by bistatic theory. Further analysis of the data revealed that the system is limited by the signal-to-interference ratio (SIR), and not the signal-to-noise ratio. We have also shown that a new interference suppression technique based on the CLEAN algorithm can improve the SIR by approximately 19 dB. These encouraging initial findings demonstrate the potential for using passive WiFi radar as a low-cost TTW detection sensor with widespread applicability.

Passive bistatic WiMAX radar for marine surveillance

In this study we investigate the feasibility of using passive bistatic radar to exploit WiMAX communication signals as transmitters of opportunity for marine surveillance. The range and Doppler characteristics of such a system are first assessed through ambiguity function analysis on a typical set of WiMAX data transmission waveforms. Theoretical simulations are then used to investigate the ability of passive WiMAX radar for detecting marine vessels within three busy shipping areas in the UK, and in the presence of noise and interference signals. The initial analysis shows a range resolution of 5.6 m is achievable. Additionally, the simulations demonstrate specific scenarios where WiMAX radar may be used as a low cost surveillance device for detecting both small and large marine vessels in port areas and open waters.

Target Localization with a Single Sensor via Multipath Exploitation

In urban sensing and through-the-wall (TTW) radar, the existence of targets inside buildings results in multipath returns. These multipath returns are exploited to achieve target localization with a single sensor. A time-of-arrival (TOA) wall association algorithm is derived to relate multipath returns to their respective walls and targets, followed by a nonlinear least squares (NLS) optimization to localize the targets. Simulations and experimental data are used to validate the proposed algorithms.

Ultrawideband Impulse Radar Through-the-Wall Imaging with Compressive Sensing

Compressive Sensing (CS) provides a new perspective for addressing radar applications requiring large amount of measurements and long data acquisition time; both issues are inherent in through-the-wall radar imaging (TWRI). Most CS techniques applied to TWRI consider stepped-frequency radar platforms. In this paper, the impulse radar two-dimensional (2D) TWRI problem is cast within the framework of CS and solved by the sparse constraint optimization performed on time-domain samples. Instead of the direct sampling of the time domain signal at the Nyquist rate, the Random Modulation Preintegration architecture is employed for the CS projection measurement, which significantly reduces the amount of measurement data for TWRI. Numerical results for point-like and spatially extended targets show that high-quality reliable TWRI based on the CS imaging approach can be achieved with a number of data points with an order of magnitude less than that required by conventional beamforming using the entire data volume.

Factors influencing antibody stability at solid–liquid interfaces in a high shear environment

A rotating disk shear device was used to study the effect of interfacial shear on the structural integrity of human monoclonal antibodies of IgG4 isotype. Factors associated with the solution conditions (pH, ionic strength, surfactant concentration, temperature) and the interface (surface roughness) were studied for their effect on the rate of IgG4 monomer loss under high shear conditions. The structural integrity of the IgG4 was probed after exposure to interfacial shear effects by SDS‐PAGE, IEF, dynamic light scattering, and peptide mapping by LC‐MS. This analysis revealed that the main denaturation pathway of IgG4 exposed to these effects was the formation of large insoluble aggregates. Soluble aggregation, breakdown in primary structure, and chemical modifications were not detected. The dominant factors found to affect the rate of IgG4 monomer loss under interfacial shear conditions were found to be pH and the nanometer‐scale surface roughness associated with the solid‐liquid interface. Interestingly, temperature was not found to be a significant factor in the range tested (15–45°C). The addition of surfactant was found to have a significant stabilizing effect at concentrations up to 0.02% (w/v). Implications of these findings for the bioprocessing of this class of therapeutic protein are briefly discussed.

Radar Micro-Doppler Signature Classification using Dynamic Time Warping

This paper describes the first feasibility study using dynamic time warping (DTW) to classify the micro-Doppler signature (μ-DS ) for radar automatic target recognition (ATR). Real radar data has been used in the testing, and the performance of the DTW classifier has been benchmarked against the conventional k-nearest neighbour (k-NN) algorithm. The basic theory behind the μ-DS is introduced, and aspects of the phenomenon that could cause difficulties for classifiers are highlighted. We explain how DTW can cope with these difficulties and achieve successful classification of three target classes. A correct classification rate exceeding 0.8 has been achieved, leading to the conclusion that this technique shows considerable promise for application in radar ATR systems.

Robust Through-the-Wall Radar Image Classification Using a Target-Model Alignment Procedure

A through-the-wall radar image (TWRI) bears little resemblance to the equivalent optical image, making it difficult to interpret. To maximize the intelligence that may be obtained, it is desirable to automate the classification of targets in the image to support human operators. This paper presents a technique for classifying stationary targets based on the high-range resolution profile (HRRP) extracted from 3-D TWRIs. The dependence of the image on the target location is discussed using a system point spread function (PSF) approach. It is shown that the position dependence will cause a classifier to fail, unless the image to be classified is aligned to a classifier-training location. A target image alignment technique based on deconvolution of the image with the system PSF is proposed. Comparison of the aligned target images with measured images shows the alignment process introducing normalized mean squared error (NMSE) ≤ 9%. The HRRP extracted from aligned target images are classified using a naive Bayesian classifier supported by principal component analysis. The classifier is tested using a real TWRI of canonical targets behind a concrete wall and shown to obtain correct classification rates ≥97%.

Template Based Micro-Doppler Signature Classification

The micro-Doppler signature of a target is a time varying frequency modulation imparted on the radar echo signal by moving components of the target. Battlefield radar output the baseband signal as audio and soldiers listening on headphones are able to identify the target from its micro-Doppler signature. Automation of this capability is desirable for improved reliability and reduction in classification time. For the first time dynamic time warping (DTW), a speech recognition technique, has been applied to the problem. Its performance has been compared with the common k-nearest neighbour (k-NN) classification method since both approaches utilise a template library

Target detection in high clutter using passive bistatic WiFi radar

The rapid rollout of wireless local area networks (WLANs) has provided a ubiquitous source of signal transmissions that may be exploited for surveillance applications using passive bistatic radar (PBR) and passive multistatic radar (PMR) systems. In this study, a series of experiments were conducted to examine the feasibility of using IEEE 802.11 wireless fidelity (WiFi) transmissions for detecting uncooperative targets in high clutter indoor environments. The range and Doppler characteristics of the system were also assessed theoretically from an ambiguity function analysis on WiFi signals having similar transmission parameters. Through-wall detections of personnel targets moving at differing velocities within an indoor environment are presented for the first time. The work demonstrates the feasibility for developing a low cost surveillance device that utilises WiFi networks as transmitters of opportunity.

Compressed Sampling for pulse Doppler radar

This paper presents a study of how the Analogue to Digital Converter (ADC) sampling rate in a digital radar can be reduced-without reduction in waveform bandwidth-through the use of Compressed Sampling (CS). Real radar data is used to show that through use of chirp or Gabor dictionaries and Basis Pursuit (BP) the ADC sampling frequency can be reduced by a factor of 128, to under 1 mega sample per second, while the waveform bandwidth remains 40 MHz. The error on the reconstructed fast-time samples is small enough that accurate range-profiles and range-frequency surfaces can be produced.