Bart Scheers

Estimating soil electric properties from monostatic ground‐penetrating radar signal inversion in the frequency domain

[1] A new integrated approach for identifying the shallow subsurface electric properties from ground-penetrating radar (GPR) signal is proposed. It is based on an ultrawide band (UWB) stepped frequency continuous wave (SFCW) radar combined with a dielectric filled transverse electric and magnetic (TEM) horn antenna to be used off the ground in monostatic mode; that is, a single antenna is used as emitter and receiver. This radar configuration is appropriate for subsurface mapping and allows for an efficient and more realistic modeling of the radar-antenna-subsurface system. Forward modeling is based on linear system response functions and on the exact solution of the three-dimensional Maxwell equations for wave propagation in a horizontally multilayered medium representing the subsurface. Subsurface electric properties, i.e., dielectric permittivity and electric conductivity, are estimated by model inversion using the global multilevel coordinate search optimization algorithm combined sequentially with the local Nelder-Mead simplex algorithm (GMCS-NMS). Inversion of synthetic data and analysis of the corresponding response surfaces proved the uniqueness of the inverse solution. Laboratory experiments on a tank filled with a homogeneous sand subject to different water content levels further demonstrated the stability and accuracy of the solution toward measurement and modeling errors, particularly those associated with the dielectric permittivity. Inversion for the electric conductivity led to less satisfactory results. This was mainly attributed to the characterization of the frequency response of the antenna and to the high frequency dependence of the electric conductivity.

Performance analysis of unslotted CSMA/CA in wireless networks

In this paper a novel analytical model for the saturation throughput of unslotted Carrier Sensing Multiple Access with Collision Avoidance (CSMA/CA) in wireless networks is proposed. A fixed point procedure is developed based on the interaction of the Physical layer (PHY) and the Medium Access Control sub-layer (MAC). The output of the Clear Channel Assessment (CCA), i.e. idle or busy medium in the neighborhood of a node, serves as a feedback mechanism for the dynamical scheduling rate controlled by the back-off procedure. The PHY is described by a renewal process between successful transmissions with failed attempts and collided packets in between. A semi-Markov process of the internal states of a node is used as a model for the MAC. An event-driven simulator for the non-beacon enabled IEEE Std 802.15.4™MAC is developed to verify the numerical results of the analytical method. A detailed analysis of the idle period after a transmission is carried out based on the proposed analytical approach. The probability that the CCA senses the channel idle depends clearly on the actual back-off stage and the first back-off expiration after a transmission cannot be modeled by a exponential distribution when a finite number of nodes are in contention. The output of the event-driven simulations confirms both statements in great detail and the saturated throughput evaluated with the analytical procedure is verified by event-driven simulations.

GPR design and modeling for identifying the shallow subsurface dielectric properties

A ground penetrating radar (GPR) system for identifying the shallow subsurface dielectric properties is proposed. It consists in a stepped frequency continuous wave (SFCW) radar operating in the 0.8-4 GHz ultrawide band combined with a dielectric filled TEM horn antenna to be used off ground in monostatic mode. This radar configuration is of practical interest since it responds to subsurface mapping requirements and allows for an efficient and realistic modeling of the radar-antenna-subsurface system. Forward modeling of the system is based on linear system response functions and on the exact solution of the three-dimensional Maxwell equations for damped wave propagation in a horizontally multilayered medium representing the shallow subsurface. The model is validated under controlled laboratory conditions. This model is destined to be inverted to reconstruct the depth dependent shallow subsurface dielectric properties from field observations.

Laboratory UWB GPR system for land mine detection

In this paper, the design and the modeling of an indoor impulse UWB GPR systems (1 GHz - 5 GHz), built in the scope of the HUDEM project, is presented. For an impulse UWB system, a time-domain modeling is an obvious choice. We explain how the antennas can be characterized by their normalized impulse response. By considering the antenna as a convolution operator, we get a mechanism for modeling the whole radar system as a cascade of linear responses, which gives a lot of advantages and possible application. In our research it is used to express the radar range equation in the time-domain, to optimize the antenna configuration and to tune signal- processing algorithms. The deconvolution of the signal source and antenna impulse responses is an ill posed operation. In this paper we present a method for decomposing an A-scan in a linear combination of wavelets, using the Continuous Wavelet Transformations -- by properly choosing the mother wavelet. This technique can also be used to reduce the amount of data for further processing. Finally results obtained by our UWB GPR system are shown. Advantages and shortcomings are discussed.

Migration technique based on the time-domain model of the Ground Penetrating Radar

Migration is a common name for processing techniques that try to reconstruct, from the dat recorded at the surface, the reflecting structures in the sub-surface. Most of the existing migration techniques do not take into account the characteristics of the acquisition system and the ground characteristics. We propose a novel migration method, applicable on Ground Penetrating Radar (GPR) images, that integrates the time domain model of the GPR in the migration scheme. We calculate by forward modeling a synthetic 3D point spread function of the GPR, i.e. a synthetic C-scan of a small point scatterer. The 3D point spread function, containing system characteristics like the waveform of the excitation source, the combined antenna footprint and the impulse response (IR) of the antennas, is then used to deconvolve the recorded data. Results of this migration method on real data obtained by an ultra-wideband GPR system show that the migration method is able to reconstruct the top contour of small targets like AP mines, in some cases even the correct dimensions. The method is also capable of migrating oblique targets into their true position. The migration scheme is not computational intensive and can easily be implemented in real time.

Jamming mitigation in cognitive radio networks using a modified Q-learning algorithm

The jamming attack is one of the most severe threats in cognitive radio networks, because it can lead to network degradation and even denial of service. However, a cognitive radio can exploit its ability of dynamic spectrum access and its learning capabilities to avoid jammed channels. In this paper, we study how Q-learning can be used to learn the jammer strategy in order to pro-actively avoid jammed channels. The problem with Q-learning is that it needs a long training period to learn the behavior of the jammer. To address the above concern, we take advantage of the wideband spectrum sensing capabilities of the cognitive radio to speed up the learning process and we make advantage of the already learned information to minimize the number of collisions with the jammer during training. The effectiveness of this modified algorithm is evaluated by simulations in the presence of different jamming strategies and the simulation results are compared to the original Q-learning algorithm applied to the same scenarios.

Autonomous dynamic spectrum management for coexistence of multiple cognitive tactical radio networks

In this paper, dynamic spectrum management is studied for multiple cognitive tactical radio networks coexisting in the same area. A tactical radio network is composed of a transmitter which broadcasts the same information to its multiple receivers. First, we consider the problem of power minimization subject to a minimum rate constraint and a spectral mask constraint for a single tactical radio network with multiple receivers over parallel channels (parallel multicast channels). Then, we extend the iterative waterfilling algorithm to multiple receivers for the coexistence of multiple cognitive tactical radio networks, meaning that there is no cooperation between the different networks. The power allocation is performed autonomously at the transmit side assuming knowledge of the noise variances and channel variations of the network. Simulation results show that the proposed algorithm is very robust in satisfying these constraints while minimizing the overall power in various scenarios.

Pseudo-Random Binary Sequence Selection for Delay and Add Direct Sequence Spread Spectrum Modulation Scheme

Recently, correlation delay shift keying (CDSK) has been proposed as a modulation scheme for noncoherent detection which inherits the advantages of conventional spread-spectrum communications using a chaotic reference signal. The CDSK modulation scheme transmits the sum of a chaotic reference signal with its delayed modulated version. In this paper, we consider the utilisation of pseudo-random binary sequences (PRBS) instead of chaotic reference signals. This new modulation scheme is defined as the delay and add direct sequence (DADS) modulation scheme. DADS offers some interesting properties compared to CDSK, mainly the possibility to select some PRBS which improves the BER performance. To this end, a new criterion for PRBS selection is proposed. Theoretical analysis and simulation results show that the BER performance of CDSK is comparable to DADS with arbitrary PRBS, however the DADS performance can be improved by 3 dB with PRBS selection.

Progressive Decentralized TDMA Based MAC: Joint Optimization of Slot Allocation and Frame Lengths

The TDMA based MAC scheduling is considered appropriate for many applications in which deterministic medium access schedule plays a crucial role. The existing plentiful literature on the TDMA based scheduling focus on the conflict-free slot allocation where the scheduling problem is broken into two disjoint problems: first find conflict free slot allocation, minimizing the number of slots used, and subsequently select frame sizes in which to use the assigned slots. In this paper, we show that such a sequential approach could lead to suboptimal performance when analyzed from the perspective of slot or channel reuse, which is the prime objective of the spatial reuse TDMA schemes. To his end, we formulate the channel scheduling as an optimization problem that aims to maximize the slot reuse factor whereby we jointly optimize the slots assignment and the frame lengths. The problem being inherently NP-hard, to solve it we propose a greedy heuristic based algorithm by which nodes complete slot assignment in a progressive decentralized way. We show that under the proposed algorithm, all nodes are guaranteed to find a conflict-free transmission schedule. Besides, we provide upper bound on the convergence time of the algorithm for a single node, and for the whole network. Finally, with simulation examples, we show that the proposed algorithm when compared with other TDMA scheduling schemes could give better performance in terms of slot reuse factor.

Dynamic channel and transmit-power adaptation of WiFi mesh-networks in search and rescue operations

For search and rescue (SAR) missions in emergency and disaster scenarios, unmanned robotic technologies offer an opportunity to save human lives and speed up the rescue process. Communication among the unmanned devices and with the command and control station plays a key role in detecting, locating, and rescuing affected persons. To establish this communication network, ease of deployment provided by the wireless communication paradigm makes it a suitable technology in any SAR mission. Lack of any infrastructure support in a disaster hit area means that the wireless network needs to be a self-organizing network of mobile devices that embodies cognitive features enabling it to adapt to the dynamics of the operational environment. To this end, we develop a framework for cognitive management and control of the WiFi mesh-networks for use in SAR operations. We propose dynamic channel and transmitpower adaptation algorithms that do not require any modification of the underlying device driver or firmware. For control signaling we can use either in-band signaling essentially using the WiFi network, or a dedicated robust narrow-band radio network. Where the latter option may be preferred in harsh propagation environments like in SAR scenarios. Effectiveness of the proposed scheme is illustrated with results from implementation with commercial of the shelf components.