Wi-Fi based people tracking in challenging environments

People tracking is a key building block in many applications such as abnormal activity detection, gesture recognition, and elderly persons monitoring. Video-based systems have many limitations making them ineffective in many situations. Wi-Fi provides an easily accessible source of opportunity for people tracking that does not have the limitations of video-based systems. The system will detect, localise, and track people, based on the available Wi-Fi signals that are reflected from their bodies. Wi-Fi based systems still need to address some challenges in order to be able to operate in challenging environments. Some of these challenges include the detection of the weak signal, the detection of abrupt people motion, and the presence of multipath propagation. In this thesis, these three main challenges will be addressed. Firstly, a weak signal detection method that uses the changes in the signals that are reflected from static objects, to improve the detection probability of weak signals that are reflected from the person’s body. Then, a deep learning based Wi-Fi localisation technique is proposed that significantly improves the runtime and the accuracy in comparison with existing techniques. After that, a quantum mechanics inspired tracking method is proposed to address the abrupt motion problem. The proposed method uses some interesting phenomena in the quantum world, where the person is allowed to exist at multiple positions simultaneously. The results show a significant improvement in reducing the tracking error and in reducing the tracking delay

Performance Limits and Geometric Properties of Array Localization

Location-aware networks are of great importance and interest in both civil and military applications. This paper determines the localization accuracy of an agent, which is equipped with an antenna array and localizes itself using wireless measurements with anchor nodes, in a far-field environment. In view of the Cram\'er-Rao bound, we first derive the localization information for static scenarios and demonstrate that such information is a weighed sum of Fisher information matrices from each anchor-antenna measurement pair. Each matrix can be further decomposed into two parts: a distance part with intensity proportional to the squared baseband effective bandwidth of the transmitted signal and a direction part with intensity associated with the normalized anchor-antenna visual angle. Moreover, in dynamic scenarios, we show that the Doppler shift contributes additional direction information, with intensity determined by the agent velocity and the root mean squared time duration of the transmitted signal. In addition, two measures are proposed to evaluate the localization performance of wireless networks with different anchor-agent and array-antenna geometries, and both formulae and simulations are provided for typical anchor deployments and antenna arrays.Comment: to appear in IEEE Transactions on Information Theor

Sparsity-based autoencoders for denoising cluttered radar signatures

Narrowband and broadband indoor radar images significantly deteriorate in the presence of target-dependent and target-independent static and dynamic clutter arising from walls. A stacked and sparse denoising autoencoder (StackedSDAE) is proposed for mitigating the wall clutter in indoor radar images. The algorithm relies on the availability of clean images and the corresponding noisy images during training and requires no additional information regarding the wall characteristics. The algorithm is evaluated on simulated Doppler-time spectrograms and high-range resolution profiles generated for diverse radar frequencies and wall characteristics in around-the-corner radar (ACR) scenarios. Additional experiments are performed on range-enhanced frontal images generated from measurements gathered from a wideband radio frequency imaging sensor. The results from the experiments show that the StackedSDAE successfully reconstructs images that closely resemble those that would be obtained in free space conditions. Furthermore, the incorporation of sparsity and depth in the hidden layer representations within the autoencoder makes the algorithm more robust to low signal-to-noise ratio (SNR) and label mismatch between clean and corrupt data during training than the conventional single-layer DAE. For example, the denoised ACR signatures show a structural similarity above 0.75 to clean free space images at SNR of −10 dB and label mismatch error of 50%

FM airborne passive radar

The airborne application of Passive Bistatic Radar (PBR) is the latest evolution of the now established international interest in passive radar techniques. An airborne passive system is cheaper to construct, easier to cool, lighter and requires less power than a traditional active radar system. These properties make it ideal for installation on an Unmanned Aerial Vehicle (UAV), especially for the next generation of Low Observable (LO) UAVs, complementing the platforms LO design with an inherently Low Probability of Intercept (LPI) air-to-air and air-to-ground sensing capability. A comprehensive literature review identified a lack of practical and theoretical research in airborne passive bistatic radar and a quantitative model was designed in order to un- derstand the theoretical performance achievable using a hypothetical system and FM as the illuminator of opportunity. The results demonstrated a useable surveillance volume, assuming conservative estimates for the receiver parameters and allowed the scoping and specification of an airborne demonstrator system. The demonstrator system was subsequently designed and constructed and flown on airborne experiments to collect data for both air-to-air and air-to-ground operation analysis. Subsequent processing demonstrated the successful detection of air targets which correlated with the actual aircraft positions as recorded by a Mode-S/ADS-B receiver. This is the first time this has been conclusively demonstrated in the literature. Doppler Beam Sharpening was used to create a coarse resolution image allowing the normalised bistatic clutter RCS of the stationary surface clutter to be analysed. This is the first time this technique has been applied to an airborne passive system and has yielded the first quantitive values of normalised bistatic clutter RCS at VHF. This successful demonstration of airborne passive radar techniques provides the proof of concept and identifies the key research areas that need to be addressed in order to fully develop this technology

1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

Radar simulation of human activities in non line-of-sight environments

textThe capability to detect, track and monitor human activities behind building walls and other non-line-of-sight environments is an important component of security and surveillance operations. Over the years, both ultrawideband and Doppler based radar techniques have been researched and developed for tracking humans behind walls. In particular, Doppler radars capture some interesting features of the human radar returns called microDopplers that arise from the dynamic movements of the different body parts. All the current research efforts have focused on building hardware sensors with very specific capabilities. This dissertation focuses on developing a physics based Doppler radar simulator to generate the dynamic signatures of complex human motions in nonline-of-sight environments. The simulation model incorporates dynamic human motion, electromagnetic scattering mechanisms, channel propagation effects and radar sensor parameters. Detailed, feature-by-feature analyses of the resulting radar signatures are carried out to enhance our fundamental understanding of human sensing using radar. First, a methodology for simulating the radar returns from complex human motions in free space is presented. For this purpose, computer animation data from motion capture technologies are exploited to describe the human movements. Next, a fast, simple, primitive-based electromagnetic model is used to simulate the human body. The microDopplers of several human motions such as walking, running, crawling and jumping are generated by integrating the animation models of humans with the electromagnetic model of the human body. Next, a methodology for generating the microDoppler radar signatures of humans moving behind walls is presented. This involves combining wall propagation functions derived from the finite-difference time-domain (FDTD) simulation with the free space radar simulations of humans. The resulting hybrid simulator of the human and wall is used to investigate the effects of both homogeneous and inhomogeneous walls on human microDopplers. The results are further corroborated by basic point-scatterer analysis of different wall effects. The wall studies are followed by an analysis of the effects of flat grounds on human radar signatures. The ground effect is modeled using the method of images and a ground reflection coefficient. A suitable Doppler radar testbed is developed in the laboratory for simulation validation. Measured data of different human activities are collected in both line-of-sight and through-wall environments and the resulting microDoppler signatures are compared with the simulation results. The human microDopplers are best observed in the joint timefrequency space. Hence, suitable joint time-frequency transforms are investigated for improving the display and the readability of both simulated and measured spectrograms. Finally, two new Doppler radar paradigms are considered. First, a scenario is considered where multiple, spatially distributed Doppler radars are used to measure the microDopplers of a moving human from different viewing angles. The possibility of using these microDoppler data for estimating the positions of different point scatterers on the human body is investigated. Second, a scenario is considered where multiple Doppler radars are collocated in a two-dimensional (2-D) array configuration. The possibility of generating frontal images of human movements using joint Doppler and 2-D spatial beamforming is considered. The performance of this concept is compared with that of conventional 2-D array processing without Doppler processing.Electrical and Computer Engineerin