A 2D processing algorithm for detecting landmines using Ground Penetrating Radar data

Ground Penetrating Radar(GPR) is one of a number of technologies that have been used to improve landmine detection efficiency. The clutter environment within the first few cm of the soil where landmines are buried, exhibits strong reflections with highly non-stationary statistics. An antipersonnel mine(AP) can have a diameter as low as 2cm whereas many soils have very high attenuation frequencies above 3GHZ. The landmine detection problem can be solved by carrying out system level analysis of the issues involved to synthesise an image which people can readily understand. The SIMCA (’SIMulated Correlation Algorithm’) is a technique that carries out correlation between the actual GPR trace that is recorded at the field and the ideal trace which is obtained by carrying out GPR simulation. The SIMCA algorithm firstly calculates by forward modelling a synthetic point spread function of the GPR by using the design parameters of the radar and soil properties to carry out radar simulation. This allows the derivation of the correlation kernel. The SIMCA algorithm then filters these unwanted components or clutter from the signal to enhance landmine detection. The clutter removed GPR B scan is then correlated with the kernel using the Pearson correlation coefficient. This results in a image which emphasises the target features and allows the detection of the target by looking at the brightest spots. Raising of the image to an odd power >2 enhances the target/background separation. To validate the algorithm, the length of the target in some cases and the diameter of the target in other cases, along with the burial depth obtained by the SIMCA system are compared with the actual values used during the experiments for the burial depth and those of the dimensions of the actual target. Because, due to the security intelligence involved with landmine detection and most authors work in collaboration with the national government military programs, a database of landmine signatures is not existant and the authors are also not able to publish fully their algorithms. As a result, in this study we have compared some of the cleaned images from other studies with the images obtained by our method, and I am sure the reader would agree that our algorithm produces a much clearer interpretable image

The SIMCA algorithm for processing Ground Penetrating Radar data and its use in landmine detection

The main challenge of ground penetrating radar (GPR) based land mine detection is to have an accurate image analysis method that is capable of reducing false alarms. However an accurate image relies on having sufficient spatial resolution in the received signal. But because the diameter of an AP mine can be as low as 2cm and many soils have very high attenuations at frequencies above 3GHz, the accurate detection of landmines is accomplished using advanced algorithms. Using image reconstruction and by carrying out the system level analysis of the issues involved with recognition of landmines allows the landmine detection problem to be solved. The SIMCA (’SIMulated Correlation Algorithm’) is a novel and accurate landmine detection tool that carries out correlation between a simulated GPR trace and a clutter1 removed original GPR trace. This correlation is performed using the MATLAB R processing environment. The authors tried using convolution and correlation. But in this paper the correlated results are presented because they produced better results. Validation of the results from the algorithm was done by an expert GPR user and 4 other general users who predict the location of landmines. These predicted results are compared with the ground truth data

A 3D Reconstruction Algorithm for the Location of Foundations in Demolished Buildings

The location of foundations in a demolished building can be accomplished by undertaking a Ground Penetrating Radar (GPR) survey and then to use the GPR data to generate 3D isosurfaces of what was beneath the soil surface using image reconstruction. The SIMCA ('SIMulated Correlation Algorithm') algorithm is a technique based on a comparison between the trace that would be returned by an ideal point reflector in the soil conditions at the site and the actual trace. During an initialization phase, SIMCA carries out radar simulation using the design parameters of the radar and the soil properties. The trace which would be returned by a target under these conditions is then used to form a kernel. Then SIMCA takes the raw data as the radar is scanned over the ground and removes clutter using a clutter removal technique. The system correlates the kernel with the data by carrying out volume correlation and produces 3D images of the surface of subterranean objects detected. The 3D isosurfaces are generated using MATLAB software. The validation of the algorithm has been accomplished by comparing the 3D isosurfaces produced by the SIMCA algorithm, Scheers algorithm and REFLEXW commercial software. Then the depth and the position in the x and y directions as obtained using MATLAB software for each of the cases are compared with the corresponding values approximately obtained from original Architect's drawings of the buildings

The SIMCA algorithm for processing Ground Penetrating Radar data and its use in locating foundations in demolished buildings

Abstract—The main challenge of ground penetrating radar GPR) based foundation detection is to have an accurate image analysis method. In order to solve the detection problem a system level analysis of the issues involved with the recognition of foundations using image reconstruction is required. The SIMCA (’SIMulated Correlation Algorithm’) is a technique based on an area correlation between the trace that would be returned by an ideal point reflector in the soil conditions at the site and the actual trace. During an initialization phase, SIMCA carries out radar simulation using the design parameters of the radar and soil properties. Then SIMCA takes the raw data as the radar is scanned over the ground and in real-time uses a clutter removal technique to remove various clutter such as cross talk, initial ground reflection and antenna ringing. The trace which would be returned by a target under these conditions is then used to form a correlation kernel. The GPR b-scan is then correlated with the kernel using the Pearson correlation coefficient, resulting in a correlated image which is brightest at points most similar to the canonical target. This image is then raised to an odd power >2 to enhance the target/background separation. To validate and compare the algorithm, photographs of the building before it was demolished along with processed data using the REFLEXW package were used. The results produced by the SIMCA algorithm were very promising and were able to locate some features that the REFLEXW package were not able to identify

Change in the room temperature magnetic property of ZnO upon Mn doping

We present in this paper the changes in the room temperature magnetic property of ZnO on Mn doping prepared using solvo-thermal process. The zero field cooled (ZFC) and field cooled (FC) magnetisation of undoped ZnO showed bifurcation and magnetic hysteresis at room temperature. Upon Mn doping the magnetic hysteresis at room temperature and the bifurcation in ZFC-FC magnetization vanishes. The results seem to indicate that undoped ZnO is ferromagnetic while on the other hand the Mn doped ZnO is not a ferromagnetic system. We observe that on addition of Mn atoms the system shows antiferromagnetism with very giant magnetic moments.Comment: 5 figure

DIVeR: a dynamic interactive video retrieval protocol for disk array based servers

Video-on-demand (VOD) is a very promising multimedia application of the near future. In order for such a service to be commercially viable, efficient storage and retrieval schemes need to be designed. A scheme for grouping MPEG frames into segments wherein no frames are discarded during fast playback is proposed. In addition, the Dynamic Interactive Video Retrieval (DIVeR) protocol is introduced for scheduling the retrieval of multiple users from disk-array servers.published_or_final_versio

QuIVeR: A class of interactive video retrieval protocols

Video-on-demand (VOD) servers need to be efficiently designed in order to support a large number of users viewing the same or different videos at different rates. In this paper, we propose the Quasi-static Interactive Video Retrieval (QuIVeR) Protocol for this purpose when disk-array based video servers are used. Five variations - QuIVeR-1, QuIVeR-2, QuIVeR-3, QuIVeR-4 and QuIVeR-5 - are presented. The properties as well as the relative merits and demerits of each protocol are discussed. The protocols require no buffer at the server and hence, all retrieved segments are immediately transmitted to the appropriate users. The amount of buffer required at each user's set-top box is reduced to two video segments. Guarantees are provided for the avoidance of video starvation as well as buffer overflow at each user's set-top box. Numerical results, obtained using data from an MPEG coded `Star Wars' video, are provided.published_or_final_versio

A perovskite oxide with high conductivities in both air and reducing atmosphere for use as electrode for solid oxide fuel cells

Electrode materials which exhibit high conductivities in both oxidising and reducing atmospheres are in high demand for solid oxide fuel cells (SOFCs) and solid oxide electrolytic cells (SOECs). In this paper, we investigated Cu-doped SrFe0.9Nb0.1O3−δ finding that the primitive perovskite oxide SrFe0.8Cu0.1Nb0.1O3−δ (SFCN) exhibits a conductivity of 63 Scm−1and 60 Scm−1 at 415 °C in air and 5%H2/Ar respectively. It is believed that the high conductivity in 5%H2/Ar is related to the exsolved Fe (or FeCu alloy) on exposure to a reducing atmosphere. To the best of our knowledge, the conductivity of SrFe0.8Cu0.1Nb0.1O3−δ in a reducing atmosphere is the highest of all reported oxides which also exhibit a high conductivity in air. Fuel cell performance using SrFe0.8Cu0.1Nb0.1O3−δ as the anode, (Y2O3)0.08(ZrO2)0.92 as the electrolyte and La0.8Sr0.2FeO3−δ as the cathode achieved a power density of 423 mWcm−2 at 700 °C indicating that SFCN is a promising anode for SOFCs

Scandium Doping Effect on a Layered Perovskite Cathode for Low-Temperature Solid Oxide Fuel Cells (LT-SOFCs)

Layered perovskite oxides are considered as promising cathode materials for the solid oxide fuel cell (SOFC) due to their high electronic/ionic conductivity and fast oxygen kinetics at low temperature. Many researchers have focused on further improving the electrochemical performance of the layered perovskite material by doping various metal ions into the B-site. Herein, we report that Sc3+ doping into the layered perovskite material, PrBaCo2O5+ (PBCO), shows a positive effect of increasing electrochemical performances. We confirmed that Sc3+ doping could provide a favorable crystalline structure of layered perovskite for oxygen ion transfer in the lattice with improved Gold-schmidt tolerance factor and specific free volume. Consequently, the Sc3+ doped PBCO exhibits a maximum power density of 0.73 W cm(-2) at 500 degrees C, 1.3 times higher than that of PBCO. These results indicate that Sc3+ doping could effectively improve the electrochemical properties of the layered perovskite material, PBCO

Electrochemical performance of YST infiltrated and fe doped YST infiltrated YSZ anodes for IT-SOFC

Donor doped and donor-acceptor co-doped strontium titanate perovskite are investigated for intermediate temperature solid oxide fuel cells (IT-SOFCs) anodes. Y0.08Sr0.88TiO3-delta and Y0.08Sr0.92Ti1-xFexO3-delta (x = 0.2, 0.4) anodes were prepared by infiltration in 65% porous yttria stabilized zirconia (YSZ) scaffolds. The microstructure and electrical conductivity of Y0.08Sr0.88TiO3-delta and Y0.08Sr0.92Ti1-xFexO3-delta strongly depends on Fe content. The conductivity of Y0.08Sr0.88TiO3-delta andY(0.08)Sr(0.92)Ti(1-x)Fe(x)O(3-delta); decreases with increasing Fe content in humidified H-2. Y0.08Sr0.88TiO3-delta, Y0.08Sr0.92Ti0.8Fe0.2O3-delta, and Y0.08Sr0.92Ti0.6Fe0.4O3-delta, anodes with a Pd/CeO2 catalyst show peak power density of 298, 421, and 321 mW cm(-2), respectively, in wet H-2 at 1073 K.open0