UWB radar sensor networks: Detection algorithms design and experimental analysis

In the last years radar sensor networks for localization and tracking in indoor environment have generated more and more interest, especially for anti-intrusion security systems. These networks often use Ultra Wide Band (UWB) technology, which consists in sending very short (few nanoseconds) impulse signals. This approach guarantees high resolution and accuracy and also other advantages such as low price, low power consumption and narrow-band interference (jamming) robustness. In this thesis the overall data processing (done in MATLAB environment) is discussed, starting from experimental measures from sensor devices, ending with the 2D visualization of targets movements over time and focusing mainly on detection and localization algorithms. Moreover, two different scenarios and both single and multiple target tracking are analyzed.

Detecting Improvised Explosive Devices Via Forward Looking Ground Penetrating Radar

Forward-looking ground penetrating radar shows promise for detection of improvised explosive devices in active war zones. Because of certain insurmountable physical limitations, post-processing algorithm development is the most popular research topic in this field. One such investigative avenue explores the worthiness of frequency analysis during data post-processing. Using the finite difference time domain numerical method, simulations are run to test both mine and clutter frequency response. Mines are found to respond strongest at low frequencies and cause periodic changes in ground penetrating radar frequency results. These results are called into question, however, when clutter, a phenomenon generally known to be random, is also found to cause periodic frequency effects. Possible causes, including simulation inaccuracy, are considered. Although the clutter models used are found to be inadequately random, specular reflections of differing periodicity are found to return from both the mine and the ground. The presence of these specular reflections offers a potential alternative method of determining a mine’s presence.

Using micropower impulse radar technology to screen for pneumothorax: an international bi-institutional study

Pneumothoraces (PTXs) are a common entity in thoracic trauma. Micropower impulse radar (MIR) has been able to detect PTXs in surgical patients. However, this technology has not been tested previously on trauma patients. The purpose of this study was to determine the sensitivity and specificity of MIR to detect clinically significant PTXs. We hypothesized that MIR technology can effectively screen trauma patients for clinically significant PTXs.

Can handheld micropower impulse radar technology be used to detect pneumothorax? Initial experience in a European trauma centre

BACKGROUND: Pneumothoraces are a common injury pattern in emergency medicine. Rapid and safe identification can reduce morbidity and mortality. A new handheld, battery powered device, the Pneumoscan (CE 561036, PneumoSonics Inc., Cleveland, OH, USA), using micropower impulse radar (MIR) technology, has recently been introduced in Europe for the rapid and reliable detection of PTX. However, this technology has not yet been tested in trauma patients. This is the first quality control evaluation to report on emergency room performance of a new device used in the trauma setting. MATERIAL AND METHODS: This study was performed at a Level I trauma centre in Switzerland. All patients with thoracic trauma and undergoing chest X-ray and CT-scan were eligible for the study. Readings were performed before the chest X-ray and CT scan. The patients had eight lung fields tested (four on each side). All readings with the Pneumoscan were performed by two junior residents in our department who had previously received an instructional tutorial of 15min. The qualitative MIR results were blinded, and stored on the device. We then compared the results of the MIR to those of the clinical examination, chest X-ray and CT-scan. RESULTS: 50 patients were included, with a mean age of 46 (SD 17) years. Seven patients presented with PTX diagnosed by CT; six of these were detected by Pneumoscan, leading to an overall sensitivity of 85.7 (95% confidence interval 42.1-99.6)%. Only two of seven PTX were found during clinical examination and on chest X-ray (sensitivity 28.6 (95% CI 3.7-71.0)%). Of the remaining 43 of 50 patients without PTX, one false-positive PTX was found by the Pneumoscan, resulting in a specificity of 97.7 (95% CI 87.7-99.9)%. DISCUSSION: The Pneumoscan is an easy to use handheld technology with reliable results. In this series, the sensitivity to detect a PTX by the Pneumoscan was higher than by clinical examination and chest X-ray. Further studies with higher case numbers and a prospective study design are needed to confirm our findings.

Geophysical Investigation of Subsurface Three-Dimensional Architecture of Icy Debris Fans With Ground Penetrating Radar in the Wrangell Mountains, Alaska

Icy debris fans have are newly-described landforms (Kochel and Trop, 2008 and 2012) as landforms developed immediately after deglaciation on Earth and similar features have been observed on Mars. Subsurface characteristics of Icy debris fans have not been previously investigated. Ground penetrating radar (GPR) was used to non-invasively investigate the subsurface characteristics of icy debris fans near McCarthy, Alaska, USA. The three fans investigated in Alaska are the East, West, and Middle fans (Kochel and Trop, 2008 and 2012) which below the Nabesna ice cap and on top of the McCarthy Creek Glacier. Icy debris fans in general are a largely unexplored suite of paraglacial landforms and processes in alpine regions. Recent field studies focused on direct observations and depositional processes. Their results showed that the fan's composition is primarily influenced by the type and frequency of depositional processes that supply the fan. Photographic studies show that the East Fan receives far more ice and snow avalanches whereas the Middle and West Fans receive fewer mass wasting events but more clastic debris is deposited on the Middle and West fan from rock falls and icy debris flows. GPR profiles and Wide-angle reflection and refraction (WARR) surveys consisting of both, common mid-point (CMP), and common shot-point (CSP) surveys investigated the subsurface geometry of the fans and the McCarthy Creek Glacier. All GPR surveys were collected in July of 2013 with 100MHz bi-static antennas. Four axial profiles and three cross-fan profiles were done on the West and Middle fans as well as the McCarthy Creek Glacier in order to investigate the relationship between the three features. GPR profiles yielded reflectors that were continuous for 10+ m and hyperbolic reflections in the subsurface. The depth to these reflections in the subsurface requires knowledge of the velocity of the subsurface. To find the velocity of the subsurface eight WARR surveys collected on the fans and on the McCarthy Creek glacier to provide information on variability of subsurface velocities. The profiles of the Middle and West fan have more reflections in their profiles compared to profiles done on the McCarthy Creek Glacier. Based on the WARR surveys, we interpret the lower energy return in the glacier to be caused by two reasons. 1) The increased attenuation due to wet ice versus drier ice and on the fan with GPR velocities >0.15m/ns. 2) Lack of interfaces in the glacier compared to those in the fans which are inferred to be produced by the alternating layers of stratified ice and lithic-rich layers. The GPR profiles on the West and Middle Fans show the shallow subsurface being dominated by lenticular reflections interpreted to be consistent with the shape of surficial deposits. The West Fan is distinguished from the Middle Fan by the nature of its reflections patterns and thicknesses of reflection packages that clearly shows the Middle fan with a greater thickness. The changes in subsurface reflections between the Middle and West Fans as well as the McCarthy Creek Glacier are thought to reflect the type and frequency of depositional processes and surrounding bedrock and talus slopes.

Detection of complex point targets with distributed assets in a MIMO radar system

The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.

Estimation of scots pine defoliation by the common pine sawfly (Diprion pini L.) using multi-temporal radar data

In 1998-2001 Finland suffered the most severe insect outbreak ever recorded, over 500,000 hectares. The outbreak was caused by the common pine sawfly (Diprion pini L.). The outbreak has continued in the study area, Palokangas, ever since. To find a good method to monitor this type of outbreaks, the purpose of this study was to examine the efficacy of multi-temporal ERS-2 and ENVISAT SAR imagery for estimating Scots pine (Pinus sylvestris L.) defoliation. Three methods were tested: unsupervised k-means clustering, supervised linear discriminant analysis (LDA) and logistic regression. In addition, I assessed if harvested areas could be differentiated from the defoliated forest using the same methods. Two different speckle filters were used to determine the effect of filtering on the SAR imagery and subsequent results. The logistic regression performed best, producing a classification accuracy of 81.6% (kappa 0.62) with two classes (no defoliation, >20% defoliation). LDA accuracy was with two classes at best 77.7% (kappa 0.54) and k-means 72.8 (0.46). In general, the largest speckle filter, 5 x 5 image window, performed best. When additional classes were added the accuracy was usually degraded on a step-by-step basis. The results were good, but because of the restrictions in the study they should be confirmed with independent data, before full conclusions can be made that results are reliable. The restrictions include the small size field data and, thus, the problems with accuracy assessment (no separate testing data) as well as the lack of meteorological data from the imaging dates.

Tracking a non-cooperative target using a Doppler radar wireless sensor network

Tracking or target localization is used in a wide range of important tasks from knowing when your flight will arrive to ensuring your mail is received on time. Tracking provides the location of resources enabling solutions to complex logistical problems. Wireless Sensor Networks (WSN) create new opportunities when applied to tracking, such as more flexible deployment and real-time information. When radar is used as the sensing element in a tracking WSN better results can be obtained; because radar has a comparatively larger range both in distance and angle to other sensors commonly used in WSNs. This allows for less nodes deployed covering larger areas, saving money. In this report I implement a tracking WSN platform similar to what was developed by Lim, Wang, and Terzis. This consists of several sensor nodes each with a radar, a sink node connected to a host PC, and a Matlab© program to fuse sensor data. I have re-implemented their experiment with my WSN platform for tracking a non-cooperative target to verify their results and also run simulations to compare. The results of these tests are discussed and some future improvements are proposed.

Does Radar Technology Support the Diagnosis of Pneumothorax? PneumoScan-A Diagnostic Point-of-Care Tool

Background. A nonrecognized pneumothorax (PTX) may become a life-threatening tension PTX. A reliable point-of-care diagnostic tool could help in reduce this risk. For this purpose, we investigated the feasibility of the use of the PneumoScan, an innovative device based on micropower impulse radar (MIR). Patients and Methods. addition to a standard diagnostic protocol including clinical examination, chest X-ray (CXR), and computed tomography (CT), 24 consecutive patients with chest trauma underwent PneumoScan testing in the shock trauma room to exclude a PTX. Results. The application of the PneumoScan was simple, quick, and reliable without functional disorder. Clinical examination and CXR each revealed one and PneumoScan three out of altogether four PTXs (sensitivity 75%, specificity 100%, positive predictive value 100%, and negative predictive value 95%). The undetected PTX did not require intervention. Conclusion. The PneumoScan as a point-of-care device offers additional diagnostic value in patient management following chest trauma. Further studies with more patients have to be performed to evaluate the diagnostic accuracy of the device.